Pricing

Pay per event + usage

Superlead ICP Scorer

Score sales leads against your Ideal Customer Profile (ICP) using AI. Submit any lead data — title, company, industry, size — and get a 0-100 fit score with band labels and plain-English explanations. Batch thousands or score one via instant API. For B2B prospecting and lead prioritization.

Pricing

Pay per event + usage

Rating

0.0

(0)

Developer

Superlative

Actor stats

Bookmarked

Total users

Monthly active users

a day ago

Last modified

FitScore - AI Lead Qualification and ICP Scoring

solidnorthsmartsolutions/fit-score

Score leads against your ICP instantly. Get a fit score (0-100), top 3 predicted objections with rebuttals, recommended sales approach, and a personalized first message.

SolidNorth Smart Solutions

Lead Scoring Engine — ICP Score Leads 0-100

ryanclinton/lead-scoring-engine

Score leads 0-100 against your Ideal Customer Profile across 6 weighted dimensions: industry, company size, services, contact presence, intent signals, and data completeness. Returns A-F grades + per-dimension notes. No API calls. $0.10/lead.

Ryan Clinton

ICP & Account Lead Scoring: Fit Scorer 0-100 for Clay

mambalabs/icp-account-lead-scoring-fit-scorer-0-100-for-clay

Scores pre-enriched companies against your Ideal Customer Profile using weighted signals. Returns a 0 to 100 fit score, A to D tier, and per-signal breakdown. Deterministic and LLM modes. Built for Clay enrichment and batch processing. MCP-ready for Claude Desktop and AI agents.

Mamba Labs

AI Lead Enrichment — Firmographics, ICP Score & Outreach

muhammadafzal/ai-lead-enrichment

Enrich a list of companies, domains, or people with firmographics, role data, an ICP-fit score, and a personalized outreach line — powered by an LLM with live web search. Turn raw lists into sales-ready leads.

Muhammad Afzal

LeadGraph (AI B2B Lead Generation & ICP Scoring)

antoniovfranco/leadgraph

AI-powered B2B lead generation with LangGraph ICP scoring, knowledge graph, and trigger signals. Scrapes LinkedIn, HackerNews, Google Maps and Apollo. Scores leads against your ICP using Groq (free) or OpenAI.

Antonio V. Franco

Website Lead Intelligence

jy-labs/website-lead-intelligence

Crawl any website and turn it into a sales-ready lead profile—no APIs needed. AI identifies industries, detects 50+ technologies, extracts emails and phones, estimates company size, and scores leads 0–100 against your ICP. Built for B2B sales teams and marketers qualifying leads at scale.

Juyeop Park

AI Lead Enricher - LLM-Powered Company Intelligence

lone_neutrino/ai-lead-enricher

Scrapes company websites and uses AI (Google Gemini) to classify industry, estimate size, detect tech stack, identify pain points, and score leads against your ICP. Turn raw URLs into sales-ready intelligence.

caio gonçalves

AI-Powered B2B Lead Extractor

dht168/ai-lead-extractor

Extract verified B2B leads with emails, LinkedIn profiles, and AI-powered ICP scoring from any company website.

华堂董

Instagram Lead Qualifier - Profile Fit Scoring

seemuapps/instagram-lead-qualifier

Score Instagram profiles as outreach and partnership leads. Get niche, account type, brand safety, a fit score against your brand brief, and a ready to send opening line for each profile.

Andrew

CRM Company Qualification & ICP Fit Agent

jacksu/public-company-qualification-agent

Qualify public company websites with evidence URLs, ICP focus-term matches, contact signals, confidence scores, and CRM-ready diagnostics.

jack su

{ "name": "superlead-icp-scorer", "version": "0.1.0", "type": "module", "description": "Score leads against your Ideal Customer Profile using AI. Get fit scores, band labels, and explanations for every lead.", "engines": { "node": ">=18.0.0" }, "dependencies": { "apify": "^3.5.2", "openai": "^4.0.0" }, "scripts": { "start": "node ./src/main.js", "test": "node --test tests/*.test.js" }, "author": "Superlative", "license": "ISC" }

FROM apify/actor-node:20 COPY package*.json ./ RUN npm --quiet set progress=false \ && npm install --omit=dev --omit=optional \ && echo "Installed NPM packages:" \ && (npm list --omit=dev --all || true) \ && echo "Node.js version:" \ && node --version \ && echo "NPM version:" \ && npm --version \ && rm -r ~/.npm COPY . ./ CMD npm start --silent

{ "actorOutputSchemaVersion": 1, "title": "Superlead ICP Scorer Output", "description": "Scored leads with ICP fit scores, band labels, and plain-English explanations.", "properties": { "allResults": { "type": "string", "title": "All Results", "description": "All scored leads with fit scores, bands, and summaries", "template": "{{links.apiDefaultDatasetUrl}}/items" } } }

{ "openapi": "3.0.3", "info": { "title": "Superlead ICP Scorer — Standby API", "description": "Score a single lead against your Ideal Customer Profile via HTTP GET. Returns a fit score (0-100), band label, and plain-English explanation.", "version": "0.1.0" }, "paths": { "/": { "get": { "summary": "Score a lead against an ICP", "description": "Score a single lead object against an Ideal Customer Profile description. Returns a fit score, band label, summary, and confidence. Supports BYOK via X-OpenRouter-Key header.", "operationId": "scoreLead", "parameters": [ { "name": "lead", "in": "query", "description": "Lead object as a JSON string (e.g. `{\"company\":\"Acme\",\"title\":\"VP Engineering\"}`).", "required": true, "schema": { "type": "string", "example": "{\"company\":\"Acme Corp\",\"title\":\"VP of Engineering\",\"industry\":\"SaaS\",\"employees\":150}" } }, { "name": "icp", "in": "query", "description": "Ideal Customer Profile description in plain English.", "required": true, "schema": { "type": "string", "example": "B2B SaaS companies with 50-500 employees. Decision makers: VP or above." } }, { "name": "model", "in": "query", "description": "LLM model to use.", "required": false, "schema": { "type": "string", "default": "openrouter/auto" } } ], "responses": { "200": { "description": "Scored lead with fit score, band, and explanation.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/ScoredLead" }, "examples": { "strongFit": { "summary": "Strong ICP fit", "value": { "id": 1, "label": "VP of Engineering at Acme Corp", "score": 85, "band": "excellent", "summary": "Strong fit: VP-level decision maker at mid-size SaaS company.", "confidence": 0.9 } }, "poorFit": { "summary": "Poor ICP fit", "value": { "id": 1, "label": "Marketing Intern at MegaRetail Inc", "score": 15, "band": "poor", "summary": "Poor fit: Junior role at large retail company, does not match SaaS or seniority criteria.", "confidence": 0.85 } } } } } }, "400": { "description": "Invalid request — missing lead, invalid JSON, or missing ICP.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Error" }, "example": { "error": "Provide 'lead' (JSON string) and 'icp' (text) query parameters." } } } }, "405": { "description": "Method not allowed — only GET is supported.", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Error" }, "example": { "error": "Method not allowed. Use GET." } } } } } } } }, "components": { "schemas": { "ScoredLead": { "type": "object", "required": ["id", "label", "score", "band", "summary", "confidence"], "properties": { "id": { "type": "integer", "description": "Row number (always 1 for single-item Standby requests)." }, "label": { "type": "string", "description": "Auto-generated lead summary." }, "score": { "type": "integer", "description": "ICP fit score from 0 to 100." }, "band": { "type": "string", "description": "Score band: excellent (80+), good (60-79), fair (40-59), poor (0-39)." }, "summary": { "type": "string", "description": "Plain-English explanation of the score." }, "confidence": { "type": "number", "description": "Data completeness confidence from 0 to 1." } } }, "Error": { "type": "object", "required": ["error"], "properties": { "error": { "type": "string", "description": "Human-readable error message." } } } } } }

{ "actorSpecification": 1, "fields": { "type": "object", "properties": { "id": { "type": "integer", "description": "Row number (1-based)" }, "input": { "type": "object", "description": "Original lead data as submitted" }, "label": { "type": "string", "description": "Auto-generated lead summary" }, "score": { "type": "integer", "description": "ICP fit score from 0 to 100" }, "band": { "type": "string", "description": "Score band: excellent, good, fair, or poor" }, "summary": { "type": "string", "description": "Plain-English explanation of the score" }, "confidence": { "type": "number", "description": "Data completeness confidence from 0 to 1" } } }, "views": { "overview": { "title": "Scored Leads", "transformation": { "fields": ["id", "label", "score", "band", "summary"] }, "display": { "component": "table", "properties": { "id": { "label": "ID", "format": "number" }, "label": { "label": "Lead", "format": "text" }, "score": { "label": "Score", "format": "number" }, "band": { "label": "Band", "format": "text" }, "summary": { "label": "Summary", "format": "text" } } } } } }

{ "title": "Superlead ICP Scorer", "description": "Paste your leads as JSON objects and describe your Ideal Customer Profile below, then click Start.", "type": "object", "schemaVersion": 1, "properties": { "leads": { "title": "Leads", "type": "array", "description": "Lead objects to score. Each lead is a JSON object with any fields (company, title, industry, employees, etc.).", "editor": "json", "prefill": [ {"company": "Acme Corp", "title": "VP of Engineering", "industry": "SaaS", "employees": 150}, {"company": "MegaRetail Inc", "title": "Marketing Intern", "industry": "Retail", "employees": 50000} ] }, "icp": { "title": "Ideal Customer Profile", "type": "string", "description": "Describe your ideal customer in plain English. Include company size, industry, job titles, geography, funding stage, or any other criteria.", "editor": "textarea", "prefill": "B2B SaaS companies with 50-500 employees. Series A to C funding. Decision makers: VP or above in Engineering or Product. North America." }, "model": { "sectionCaption": "Advanced", "title": "AI model", "type": "string", "description": "AI model for scoring. Default auto-routes for best price/performance. Set a specific model like google/gemini-2.0-flash-001 for more consistent scores. Browse models at openrouter.ai/models.", "default": "openrouter/auto", "editor": "textfield" }, "openRouterApiKey": { "title": "OpenRouter API key (bring your own)", "type": "string", "description": "Optional. Provide your own OpenRouter API key to use the direct OpenRouter API instead of the built-in Apify integration. Get your key at openrouter.ai.", "editor": "textfield", "isSecret": true }, "lead": { "title": "Lead (single)", "type": "object", "description": "Single lead object to score — shorthand for API/integration callers. If both 'lead' and 'leads' are provided, 'lead' is prepended to the list.", "editor": "json", "sectionCaption": "API shorthand", "sectionDescription": "For API and integration callers (Clay, Make, n8n) who want to pass a single lead without wrapping it in an array." } }, "required": ["icp"] }

{ "actorSpecification": 1, "name": "superlead-icp-scorer", "title": "Superlead ICP Scorer", "description": "Score leads against your Ideal Customer Profile using AI. Input: any JSON lead objects + ICP description. Output: {score 0-100, band, summary, confidence}. Batch or instant API.", "version": "0.1", "buildTag": "latest", "usesStandbyMode": true, "webServerSchema": "./web_server_openapi.json", "dockerfile": "./Dockerfile", "input": "./input_schema.json", "output": "./output_schema.json", "storages": { "dataset": "./dataset_schema.json" }, "defaultRunOptions": { "build": "latest", "memoryMbytes": 256, "timeoutSecs": 360 }, "minMemoryMbytes": 256, "maxMemoryMbytes": 1024 }

1#!/usr/bin/env node 2 3/** 4 * Build test fixtures from real LinkedIn + GMaps data. 5 * Converts raw scraped profiles/businesses into lead objects for ICP scoring tests. 6 * 7 * Usage: node tests/build-fixtures.js 8 * Source: ~/apify-dev/superclean-test-data/ 9 * Output: tests/fixtures/leads_linkedin.json, tests/fixtures/leads_gmaps.json 10 */ 11 12import { readFileSync, writeFileSync } from 'node:fs'; 13import { resolve, dirname } from 'node:path'; 14import { fileURLToPath } from 'node:url'; 15 16const __dirname = dirname(fileURLToPath(import.meta.url)); 17const DATA_DIR = resolve(__dirname, '../../superclean-test-data'); 18 19function convertLinkedIn(profile) { 20 const pos = profile.currentPositions?.[0] || {}; 21 const name = [profile.firstName, profile.lastName].filter(Boolean).join(' ').trim(); 22 const lead = { name }; 23 if (pos.title) lead.title = pos.title; 24 if (pos.companyName) lead.company = pos.companyName; 25 if (profile.location?.linkedinText) lead.location = profile.location.linkedinText; 26 if (pos.tenureAtCompany?.numYears != null) { 27 lead.yearsAtCompany = pos.tenureAtCompany.numYears + (pos.tenureAtCompany.numMonths || 0) / 12; 28 lead.yearsAtCompany = Math.round(lead.yearsAtCompany * 10) / 10; 29 } 30 // Include summary excerpt if present (first 200 chars) 31 if (profile.summary) { 32 lead.summary = profile.summary.slice(0, 200); 33 } 34 return lead; 35} 36 37function convertGMaps(biz) { 38 return { 39 company: biz.title, 40 industry: biz.categoryName || 'Unknown', 41 location: [biz.city, biz.state].filter(Boolean).join(', '), 42 description: biz.description || null, 43 website: biz.website || null, 44 rating: biz.totalScore || null, 45 reviewCount: biz.reviewsCount || 0, 46 }; 47} 48 49// Load and convert LinkedIn 50const engProfiles = JSON.parse(readFileSync(`${DATA_DIR}/linkedin_eng.json`, 'utf8')); 51const salesProfiles = JSON.parse(readFileSync(`${DATA_DIR}/linkedin_sales.json`, 'utf8')); 52const fullProfiles = JSON.parse(readFileSync(`${DATA_DIR}/linkedin_full.json`, 'utf8')); 53const miscProfiles = JSON.parse(readFileSync(`${DATA_DIR}/linkedin_misc.json`, 'utf8')); 54 55const linkedinLeads = [ 56 ...engProfiles.map(p => ({ ...convertLinkedIn(p), _source: 'eng' })), 57 ...salesProfiles.map(p => ({ ...convertLinkedIn(p), _source: 'sales' })), 58 ...fullProfiles.map(p => ({ ...convertLinkedIn(p), _source: 'full' })), 59 ...miscProfiles.map(p => ({ ...convertLinkedIn(p), _source: 'misc' })), 60]; 61 62// Load and convert GMaps (first 20 only — enough for testing) 63const gmapsBiz = JSON.parse(readFileSync(`${DATA_DIR}/gmaps_full.json`, 'utf8')); 64const gmapsLeads = gmapsBiz.slice(0, 20).map(convertGMaps); 65 66writeFileSync( 67 resolve(__dirname, 'fixtures/leads_linkedin.json'), 68 JSON.stringify(linkedinLeads, null, 2) + '\n' 69); 70writeFileSync( 71 resolve(__dirname, 'fixtures/leads_gmaps.json'), 72 JSON.stringify(gmapsLeads, null, 2) + '\n' 73); 74 75console.log(`LinkedIn leads: ${linkedinLeads.length}`); 76console.log(`GMaps leads: ${gmapsLeads.length}`); 77console.log('Written to tests/fixtures/');

1#!/usr/bin/env node 2 3/** 4 * Standby Integration Tests — Superlead ICP Scorer 5 * 6 * Tests the live Standby API for correct output format, scoring behavior, 7 * edge cases, and error handling. 8 * 9 * Tests are split into two groups: 10 * - Non-LLM tests: always run (landing page, error handling, validation) 11 * - LLM tests: require the OpenRouter proxy to be working; auto-skipped if unavailable 12 * 13 * Usage: 14 * node tests/standby.test.js 15 * OPENROUTER_KEY=sk-or-... node tests/standby.test.js # Run LLM tests with BYOK 16 * STANDBY_URL=http://localhost:3000 node tests/standby.test.js 17 */ 18 19import { readFileSync } from 'node:fs'; 20 21const STANDBY_URL = process.env.STANDBY_URL 22 || 'https://superlativetech--superlead-icp-scorer.apify.actor'; 23const TOKEN = process.env.APIFY_TOKEN || (() => { 24 try { 25 return JSON.parse(readFileSync(`${process.env.HOME}/.apify/auth.json`, 'utf8')).token; 26 } catch { return null; } 27})(); 28const OPENROUTER_KEY = process.env.OPENROUTER_KEY || null; 29 30let passed = 0; 31let failed = 0; 32let skipped = 0; 33const failures = []; 34 35function test(name, fn) { 36 return fn().then(() => { 37 passed++; 38 console.log(` \u2713 ${name}`); 39 }).catch((err) => { 40 failed++; 41 failures.push({ name, error: err.message }); 42 console.log(` \u2717 ${name}: ${err.message}`); 43 }); 44} 45 46function skip(name) { 47 skipped++; 48 console.log(` \u2014 ${name} (skipped: LLM proxy unavailable)`); 49} 50 51function assert(condition, message) { 52 if (!condition) throw new Error(message); 53} 54 55const TEST_ICP = 'B2B SaaS companies with 50-500 employees. Decision makers: VP or above in Engineering or Product.'; 56 57async function query(lead, icp = TEST_ICP, params = {}) { 58 const searchParams = new URLSearchParams({ lead: JSON.stringify(lead), icp, ...params }); 59 if (TOKEN) searchParams.set('token', TOKEN); 60 const url = `${STANDBY_URL}?${searchParams}`; 61 const headers = {}; 62 if (OPENROUTER_KEY) headers['X-OpenRouter-Key'] = OPENROUTER_KEY; 63 const res = await fetch(url, { signal: AbortSignal.timeout(30000), headers }); 64 const data = await res.json().catch(() => null); 65 return { status: res.status, data, headers: res.headers }; 66} 67 68async function queryRaw(path = '', params = {}) { 69 const searchParams = new URLSearchParams(params); 70 if (TOKEN) searchParams.set('token', TOKEN); 71 const qs = searchParams.toString(); 72 const url = `${STANDBY_URL}${path}${qs ? `?${qs}` : ''}`; 73 const res = await fetch(url, { signal: AbortSignal.timeout(15000) }); 74 return { status: res.status, contentType: res.headers.get('content-type'), body: await res.text() }; 75} 76 77// --------------------------------------------------------------------------- 78// Probe: check if LLM proxy is working 79// --------------------------------------------------------------------------- 80let llmAvailable = false; 81try { 82 const probe = await query({ company: 'Test Inc.', title: 'CEO' }); 83 if (probe.status === 200 && typeof probe.data?.score === 'number') { 84 llmAvailable = true; 85 } 86} catch { /* LLM unavailable */ } 87 88console.log('\n=== Superlead ICP Scorer — Standby Tests ==='); 89console.log(`BYOK: ${OPENROUTER_KEY ? 'yes' : 'no'}`); 90console.log(`LLM proxy: ${llmAvailable ? 'available' : 'UNAVAILABLE (LLM tests will be skipped)'}\n`); 91 92// --------------------------------------------------------------------------- 93// Non-LLM tests (always run) 94// --------------------------------------------------------------------------- 95 96console.log('Landing Page & Error Handling:'); 97 98await test('Landing page returned when no params', async () => { 99 const { status, contentType, body } = await queryRaw('/'); 100 assert(status === 200, `Expected 200, got ${status}`); 101 assert(contentType.includes('text/html'), `Expected HTML, got ${contentType}`); 102 assert(body.includes('Superlead'), `Landing page should mention Superlead`); 103 assert(body.includes('ICP'), `Landing page should mention ICP`); 104}); 105 106await test('Missing lead returns 400', async () => { 107 const { status, body } = await queryRaw('/', { icp: TEST_ICP }); 108 const data = JSON.parse(body); 109 assert(status === 400, `Expected 400, got ${status}`); 110 assert(data.error.includes('lead'), `Expected lead error: ${data.error}`); 111}); 112 113await test('Missing icp returns 400', async () => { 114 const searchParams = new URLSearchParams({ lead: '{"company":"Test"}' }); 115 if (TOKEN) searchParams.set('token', TOKEN); 116 const res = await fetch(`${STANDBY_URL}?${searchParams}`, { signal: AbortSignal.timeout(15000) }); 117 assert(res.status === 400, `Expected 400, got ${res.status}`); 118 const data = await res.json(); 119 assert(data.error.includes('icp'), `Expected icp error: ${data.error}`); 120}); 121 122await test('Invalid JSON in lead returns 400', async () => { 123 const searchParams = new URLSearchParams({ lead: 'not-json', icp: TEST_ICP }); 124 if (TOKEN) searchParams.set('token', TOKEN); 125 const res = await fetch(`${STANDBY_URL}?${searchParams}`, { signal: AbortSignal.timeout(15000) }); 126 assert(res.status === 400, `Expected 400, got ${res.status}`); 127 const data = await res.json(); 128 assert(data.error.includes('Invalid JSON'), `Expected JSON error: ${data.error}`); 129}); 130 131await test('Array lead returns 400', async () => { 132 const searchParams = new URLSearchParams({ lead: '[1,2,3]', icp: TEST_ICP }); 133 if (TOKEN) searchParams.set('token', TOKEN); 134 const res = await fetch(`${STANDBY_URL}?${searchParams}`, { signal: AbortSignal.timeout(15000) }); 135 assert(res.status === 400, `Expected 400, got ${res.status}`); 136 const data = await res.json(); 137 assert(data.error.includes('object'), `Expected object error: ${data.error}`); 138}); 139 140// --------------------------------------------------------------------------- 141// LLM-dependent tests (skip if proxy unavailable) 142// --------------------------------------------------------------------------- 143 144console.log('\nOutput Format (LLM):'); 145 146if (llmAvailable) { 147 await test('Returns {id, input, label, score, band, summary, confidence}', async () => { 148 const leadObj = { company: 'Acme Corp', title: 'VP of Engineering', industry: 'SaaS', employees: 150 }; 149 const { data } = await query(leadObj); 150 assert(typeof data.id === 'number', `id should be number, got ${typeof data.id}`); 151 assert(data.id === 1, `id should be 1, got ${data.id}`); 152 assert(typeof data.input === 'object' && data.input !== null, 'input should be object'); 153 assert(data.input.company === 'Acme Corp', `input.company should echo back, got ${data.input.company}`); 154 assert(typeof data.label === 'string', 'label should be string'); 155 assert(typeof data.score === 'number', 'score should be number'); 156 assert(typeof data.band === 'string', 'band should be string'); 157 assert(typeof data.summary === 'string', 'summary should be string'); 158 assert(typeof data.confidence === 'number', 'confidence should be number'); 159 assert(Object.keys(data).length === 7, `Expected 7 fields, got ${Object.keys(data).length}`); 160 }); 161 162 await test('Score is 0-100 integer', async () => { 163 const { data } = await query({ company: 'Test Corp', title: 'CEO', industry: 'SaaS', employees: 200 }); 164 assert(data.score >= 0 && data.score <= 100, `Score ${data.score} out of range`); 165 assert(Number.isInteger(data.score), `Score should be integer, got ${data.score}`); 166 }); 167 168 await test('Band matches score', async () => { 169 const { data } = await query({ company: 'Startup Inc', title: 'CTO', industry: 'SaaS', employees: 100 }); 170 const expectedBand = data.score >= 80 ? 'excellent' : data.score >= 60 ? 'good' : data.score >= 40 ? 'fair' : 'poor'; 171 assert(data.band === expectedBand, `Band "${data.band}" doesn't match score ${data.score} (expected "${expectedBand}")`); 172 }); 173 174 await test('Confidence is 0-1 range', async () => { 175 const { data } = await query({ company: 'Test', title: 'Engineer' }); 176 assert(data.confidence >= 0 && data.confidence <= 1, `Confidence ${data.confidence} out of range`); 177 }); 178 179 await test('Label generated from lead fields', async () => { 180 const { data } = await query({ company: 'Acme Corp', title: 'VP of Engineering' }); 181 assert(data.label.includes('Acme Corp'), `Label should include company: ${data.label}`); 182 }); 183 184 console.log('\nScoring Quality (LLM):'); 185 186 await test('Strong ICP match scores high', async () => { 187 const { data } = await query({ company: 'DataFlow', title: 'VP of Engineering', industry: 'SaaS', employees: 200, funding: 'Series B' }); 188 assert(data.score >= 60, `Expected high score for strong match, got ${data.score}`); 189 }); 190 191 await test('Poor ICP match scores low', async () => { 192 const { data } = await query({ company: 'MegaRetail Inc', title: 'Marketing Intern', industry: 'Retail', employees: 50000 }); 193 assert(data.score <= 50, `Expected low score for poor match, got ${data.score}`); 194 }); 195 196 console.log('\nPerformance (LLM):'); 197 198 await test('Response under 15 seconds', async () => { 199 const start = Date.now(); 200 await query({ company: 'Test Corp', title: 'CTO', industry: 'SaaS' }); 201 const duration = Date.now() - start; 202 assert(duration < 15000, `Took ${duration}ms, expected under 15s`); 203 }); 204} else { 205 skip('Returns {id, input, label, score, band, summary, confidence}'); 206 skip('Score is 0-100 integer'); 207 skip('Band matches score'); 208 skip('Confidence is 0-1 range'); 209 skip('Label generated from lead fields'); 210 console.log('\nScoring Quality (LLM):'); 211 skip('Strong ICP match scores high'); 212 skip('Poor ICP match scores low'); 213 console.log('\nPerformance (LLM):'); 214 skip('Response under 15 seconds'); 215} 216 217// --------------------------------------------------------------------------- 218// Report 219// --------------------------------------------------------------------------- 220 221console.log(`\n=== Standby Test Results ===`); 222console.log(`Passed: ${passed}, Failed: ${failed}, Skipped: ${skipped}`); 223if (failures.length > 0) { 224 console.log('\nFailures:'); 225 for (const f of failures) { 226 console.log(` ${f.name}: ${f.error}`); 227 } 228} 229const result = failed === 0 ? (skipped > 0 ? 'PASS (with skips)' : 'PASS') : 'FAIL'; 230console.log(`\nRESULT: ${result}`); 231process.exit(failed === 0 ? 0 : 1);

1#!/usr/bin/env node 2 3/** 4 * Batch Integration Tests — Superlead ICP Scorer 5 * 6 * Runs real LinkedIn and Google Maps data through the actor via the 7 * actor-tasks API endpoint (which has the saved openRouterApiKey). 8 * 9 * Test categories: 10 * 1. Format validation — every output field has correct type and range 11 * 2. Scoring quality — leads matching the ICP score higher than non-matches 12 * 3. Data variety — different lead formats and data richness levels 13 * 4. Edge cases — sparse data, wrapped format, single-lead shorthand 14 * 5. Cross-ICP — same leads scored against different ICPs produce different results 15 * 16 * Usage: 17 * node tests/batch.test.js 18 * node tests/batch.test.js --quick # Run only small-batch tests (~5 leads) 19 */ 20 21import { readFileSync } from 'node:fs'; 22import { resolve, dirname } from 'node:path'; 23import { fileURLToPath } from 'node:url'; 24 25const __dirname = dirname(fileURLToPath(import.meta.url)); 26 27// --------------------------------------------------------------------------- 28// Config 29// --------------------------------------------------------------------------- 30 31const TASK_ID = 'd8SOKHG7oxeVBEBa7'; 32const APIFY_TOKEN = process.env.APIFY_TOKEN || (() => { 33 try { 34 return JSON.parse(readFileSync(`${process.env.HOME}/.apify/auth.json`, 'utf8')).token; 35 } catch { return null; } 36})(); 37const API_BASE = 'https://api.apify.com/v2'; 38const QUICK_MODE = process.argv.includes('--quick'); 39const RUN_TIMEOUT_MS = 120_000; // 2 min per run 40const POLL_INTERVAL_MS = 3_000; 41 42if (!APIFY_TOKEN) { 43 console.error('APIFY_TOKEN not found. Set env var or log in with: apify login'); 44 process.exit(1); 45} 46 47// --------------------------------------------------------------------------- 48// Test harness 49// --------------------------------------------------------------------------- 50 51let passed = 0; 52let failed = 0; 53let skipped = 0; 54const failures = []; 55 56function assert(condition, message) { 57 if (!condition) throw new Error(message); 58} 59 60async function test(name, fn) { 61 try { 62 await fn(); 63 passed++; 64 console.log(` ✓ ${name}`); 65 } catch (err) { 66 failed++; 67 failures.push({ name, error: err.message }); 68 console.log(` ✗ ${name}: ${err.message}`); 69 } 70} 71 72function skipTest(name, reason) { 73 skipped++; 74 console.log(` — ${name} (skipped: ${reason})`); 75} 76 77// --------------------------------------------------------------------------- 78// Apify API helpers 79// --------------------------------------------------------------------------- 80 81async function runTask(input, timeoutMs = RUN_TIMEOUT_MS) { 82 const res = await fetch(`${API_BASE}/actor-tasks/${TASK_ID}/runs?token=${APIFY_TOKEN}`, { 83 method: 'POST', 84 headers: { 'Content-Type': 'application/json' }, 85 body: JSON.stringify(input), 86 }); 87 if (!res.ok) { 88 const body = await res.text(); 89 throw new Error(`Failed to start task run: ${res.status} ${body}`); 90 } 91 const { data: run } = await res.json(); 92 93 // Poll until complete 94 const deadline = Date.now() + timeoutMs; 95 while (Date.now() < deadline) { 96 await new Promise((r) => setTimeout(r, POLL_INTERVAL_MS)); 97 const statusRes = await fetch(`${API_BASE}/actor-runs/${run.id}?token=${APIFY_TOKEN}`); 98 const { data: status } = await statusRes.json(); 99 if (status.status === 'SUCCEEDED') { 100 return { runId: run.id, datasetId: status.defaultDatasetId, status: 'SUCCEEDED' }; 101 } 102 if (status.status === 'FAILED' || status.status === 'ABORTED' || status.status === 'TIMED-OUT') { 103 throw new Error(`Run ${run.id} ${status.status}`); 104 } 105 } 106 throw new Error(`Run ${run.id} timed out after ${timeoutMs}ms`); 107} 108 109async function fetchDataset(datasetId) { 110 const res = await fetch(`${API_BASE}/datasets/${datasetId}/items?token=${APIFY_TOKEN}`); 111 return res.json(); 112} 113 114// --------------------------------------------------------------------------- 115// Load fixtures 116// --------------------------------------------------------------------------- 117 118const linkedinLeads = JSON.parse(readFileSync(resolve(__dirname, 'fixtures/leads_linkedin.json'), 'utf8')); 119const gmapsLeads = JSON.parse(readFileSync(resolve(__dirname, 'fixtures/leads_gmaps.json'), 'utf8')); 120 121// Curated subsets 122const engLeads = linkedinLeads.filter((l) => l._source === 'eng'); 123const salesLeads = linkedinLeads.filter((l) => l._source === 'sales'); 124const fullLeads = linkedinLeads.filter((l) => l._source === 'full'); 125const miscLeads = linkedinLeads.filter((l) => l._source === 'misc'); 126 127// Strip _source from leads before sending (it's our metadata, not the lead data) 128function stripSource(leads) { 129 return leads.map(({ _source, ...rest }) => rest); 130} 131 132// ICP descriptions 133const ICP_SAAS_ENGINEERING = 'B2B SaaS companies with 50-500 employees. Series A to C funding. Decision makers: VP or above in Engineering or Product. North America.'; 134const ICP_ENTERPRISE_SALES = 'Enterprise companies with 1000+ employees. Sales and business development leaders. VP or Director level. Industries: Technology, Insurance, Financial Services.'; 135 136// --------------------------------------------------------------------------- 137// Format validation helpers 138// --------------------------------------------------------------------------- 139 140function validateResult(result, index) { 141 assert(typeof result.id === 'number' && result.id > 0, `[${index}] id should be positive integer, got ${result.id}`); 142 assert(typeof result.input === 'object' && result.input !== null, `[${index}] input should be object, got ${typeof result.input}`); 143 assert(typeof result.label === 'string' && result.label.length > 0, `[${index}] label should be non-empty string, got "${result.label}"`); 144 assert(typeof result.score === 'number' && Number.isInteger(result.score), `[${index}] score should be integer, got ${result.score}`); 145 assert(result.score >= 0 && result.score <= 100, `[${index}] score should be 0-100, got ${result.score}`); 146 assert(typeof result.band === 'string', `[${index}] band should be string, got ${typeof result.band}`); 147 assert(['excellent', 'good', 'fair', 'poor'].includes(result.band), `[${index}] band should be valid, got "${result.band}"`); 148 assert(typeof result.summary === 'string' && result.summary.length > 0, `[${index}] summary should be non-empty string`); 149 assert(typeof result.confidence === 'number', `[${index}] confidence should be number, got ${typeof result.confidence}`); 150 assert(result.confidence >= 0 && result.confidence <= 1, `[${index}] confidence should be 0-1, got ${result.confidence}`); 151 152 // Band must match score 153 const expectedBand = result.score >= 80 ? 'excellent' : result.score >= 60 ? 'good' : result.score >= 40 ? 'fair' : 'poor'; 154 assert(result.band === expectedBand, `[${index}] band "${result.band}" doesn't match score ${result.score} (expected "${expectedBand}")`); 155 156 // id should equal index+1 157 assert(result.id === index + 1, `[${index}] id should be ${index + 1}, got ${result.id}`); 158 159 // Exactly 7 fields 160 assert(Object.keys(result).length === 7, `[${index}] expected 7 fields, got ${Object.keys(result).length}: ${Object.keys(result).join(', ')}`); 161} 162 163// =================================================================== 164// TEST RUNS 165// =================================================================== 166 167console.log('\n=== Superlead ICP Scorer — Batch Tests ==='); 168console.log(`Mode: ${QUICK_MODE ? 'QUICK (small batches)' : 'FULL (all data)'}`); 169console.log(`LinkedIn leads: ${linkedinLeads.length} (eng: ${engLeads.length}, sales: ${salesLeads.length}, full: ${fullLeads.length}, misc: ${miscLeads.length})`); 170console.log(`GMaps leads: ${gmapsLeads.length}\n`); 171 172// --------------------------------------------------------------------------- 173// Test 1: Format validation (small batch) 174// --------------------------------------------------------------------------- 175 176console.log('Format Validation:'); 177 178const formatLeads = stripSource(engLeads.slice(0, 5)); 179let formatResults; 180 181await test('Small batch completes successfully', async () => { 182 const { datasetId } = await runTask({ leads: formatLeads, icp: ICP_SAAS_ENGINEERING }); 183 formatResults = await fetchDataset(datasetId); 184 assert(Array.isArray(formatResults), 'Dataset should be an array'); 185 assert(formatResults.length === 5, `Expected 5 results, got ${formatResults.length}`); 186}); 187 188await test('All output fields have correct types and ranges', async () => { 189 assert(formatResults, 'No results from previous test'); 190 formatResults.forEach((r, i) => validateResult(r, i)); 191}); 192 193await test('Labels contain lead info', async () => { 194 assert(formatResults, 'No results from previous test'); 195 // First lead: CHIRANJIB DAS(He/Him), Manager at Cognizant 196 const first = formatResults[0]; 197 assert(first.label.includes('Cognizant') || first.label.includes('CHIRANJIB') || first.label.includes('Manager'), 198 `Label should include lead data: "${first.label}"`); 199}); 200 201// --------------------------------------------------------------------------- 202// Test 2: Engineering leads against SaaS Engineering ICP 203// --------------------------------------------------------------------------- 204 205console.log('\nEngineering Leads vs SaaS ICP:'); 206 207let engResults; 208 209if (!QUICK_MODE) { 210 await test('25 engineering leads scored successfully', async () => { 211 const { datasetId } = await runTask({ leads: stripSource(engLeads), icp: ICP_SAAS_ENGINEERING }); 212 engResults = await fetchDataset(datasetId); 213 assert(engResults.length === 25, `Expected 25 results, got ${engResults.length}`); 214 engResults.forEach((r, i) => validateResult(r, i)); 215 }); 216 217 await test('Senior tech leaders score above average', async () => { 218 assert(engResults, 'No results from previous test'); 219 // Arun Mahajan: Senior Director at Juniper Networks, Vijay Narayanan: Director at U.S. Bank, Naga Ala: Principal Architect at Mastercard 220 const seniorLeads = engResults.filter((r) => 221 r.label.includes('Juniper') || r.label.includes('Mastercard') || r.label.includes('Naga Eskala')); 222 const avgScore = engResults.reduce((s, r) => s + r.score, 0) / engResults.length; 223 if (seniorLeads.length > 0) { 224 const seniorAvg = seniorLeads.reduce((s, r) => s + r.score, 0) / seniorLeads.length; 225 assert(seniorAvg >= avgScore * 0.8, 226 `Senior leads avg (${seniorAvg.toFixed(0)}) should be near or above batch avg (${avgScore.toFixed(0)})`); 227 } 228 }); 229 230 await test('Score distribution is reasonable', async () => { 231 assert(engResults, 'No results from previous test'); 232 const scores = engResults.map((r) => r.score); 233 const min = Math.min(...scores); 234 const max = Math.max(...scores); 235 const avg = scores.reduce((a, b) => a + b, 0) / scores.length; 236 console.log(` Score range: ${min}-${max}, avg: ${avg.toFixed(0)}`); 237 // Should have spread, not all same score 238 assert(max - min >= 15, `Score spread too narrow: ${min}-${max}`); 239 }); 240} else { 241 skipTest('25 engineering leads scored successfully', 'quick mode'); 242 skipTest('Senior tech leaders score above average', 'quick mode'); 243 skipTest('Score distribution is reasonable', 'quick mode'); 244} 245 246// --------------------------------------------------------------------------- 247// Test 3: Sales leads against SaaS Engineering ICP (expect lower scores) 248// --------------------------------------------------------------------------- 249 250console.log('\nSales Leads vs SaaS Engineering ICP:'); 251 252let salesResults; 253 254if (!QUICK_MODE) { 255 await test('25 sales leads scored successfully', async () => { 256 const { datasetId } = await runTask({ leads: stripSource(salesLeads), icp: ICP_SAAS_ENGINEERING }); 257 salesResults = await fetchDataset(datasetId); 258 assert(salesResults.length === 25, `Expected 25 results, got ${salesResults.length}`); 259 salesResults.forEach((r, i) => validateResult(r, i)); 260 }); 261 262 await test('Sales leads score lower than eng leads on SaaS Engineering ICP', async () => { 263 assert(engResults && salesResults, 'Need both eng and sales results'); 264 const engAvg = engResults.reduce((s, r) => s + r.score, 0) / engResults.length; 265 const salesAvg = salesResults.reduce((s, r) => s + r.score, 0) / salesResults.length; 266 console.log(` Eng avg: ${engAvg.toFixed(0)}, Sales avg: ${salesAvg.toFixed(0)}`); 267 assert(engAvg > salesAvg, `Engineering avg (${engAvg.toFixed(0)}) should be higher than Sales avg (${salesAvg.toFixed(0)}) for SaaS Eng ICP`); 268 }); 269} else { 270 skipTest('25 sales leads scored successfully', 'quick mode'); 271 skipTest('Sales leads score lower than eng leads on SaaS Engineering ICP', 'quick mode'); 272} 273 274// --------------------------------------------------------------------------- 275// Test 4: GMaps businesses against B2B ICP (expect poor scores) 276// --------------------------------------------------------------------------- 277 278console.log('\nGMaps Businesses vs B2B ICP (mismatch test):'); 279 280let gmapsResults; 281 282await test('20 restaurant/business leads scored successfully', async () => { 283 const { datasetId } = await runTask({ leads: gmapsLeads, icp: ICP_SAAS_ENGINEERING }); 284 gmapsResults = await fetchDataset(datasetId); 285 assert(gmapsResults.length === 20, `Expected 20 results, got ${gmapsResults.length}`); 286 gmapsResults.forEach((r, i) => validateResult(r, i)); 287}); 288 289await test('Most restaurant leads score poor or fair', async () => { 290 assert(gmapsResults, 'No results'); 291 const poorOrFair = gmapsResults.filter((r) => r.score < 60).length; 292 const pct = (poorOrFair / gmapsResults.length) * 100; 293 console.log(` ${poorOrFair}/${gmapsResults.length} scored poor/fair (${pct.toFixed(0)}%)`); 294 assert(poorOrFair >= gmapsResults.length * 0.7, 295 `Expected at least 70% poor/fair for restaurants vs B2B ICP, got ${pct.toFixed(0)}%`); 296}); 297 298await test('Average GMaps score well below engineering average', async () => { 299 assert(gmapsResults, 'No results'); 300 const gmapsAvg = gmapsResults.reduce((s, r) => s + r.score, 0) / gmapsResults.length; 301 console.log(` GMaps avg: ${gmapsAvg.toFixed(0)}`); 302 assert(gmapsAvg < 40, `GMaps avg (${gmapsAvg.toFixed(0)}) should be below 40 for B2B mismatch`); 303}); 304 305// --------------------------------------------------------------------------- 306// Test 5: Cross-ICP comparison (same leads, different ICPs) 307// --------------------------------------------------------------------------- 308 309console.log('\nCross-ICP Comparison:'); 310 311let salesIcpResults; 312const crossTestLeads = stripSource([...salesLeads.slice(0, 5), ...engLeads.slice(0, 5)]); 313 314await test('Same 10 leads scored against Enterprise Sales ICP', async () => { 315 const { datasetId } = await runTask({ leads: crossTestLeads, icp: ICP_ENTERPRISE_SALES }); 316 salesIcpResults = await fetchDataset(datasetId); 317 assert(salesIcpResults.length === 10, `Expected 10 results, got ${salesIcpResults.length}`); 318 salesIcpResults.forEach((r, i) => validateResult(r, i)); 319}); 320 321let engIcpResults; 322await test('Same 10 leads scored against SaaS Engineering ICP', async () => { 323 const { datasetId } = await runTask({ leads: crossTestLeads, icp: ICP_SAAS_ENGINEERING }); 324 engIcpResults = await fetchDataset(datasetId); 325 assert(engIcpResults.length === 10, `Expected 10 results, got ${engIcpResults.length}`); 326}); 327 328await test('Score rankings differ between ICPs', async () => { 329 assert(salesIcpResults && engIcpResults, 'Need both ICP results'); 330 // The first 5 are sales leads, last 5 are eng leads 331 const salesLeadAvg_salesIcp = salesIcpResults.slice(0, 5).reduce((s, r) => s + r.score, 0) / 5; 332 const engLeadAvg_salesIcp = salesIcpResults.slice(5, 10).reduce((s, r) => s + r.score, 0) / 5; 333 const salesLeadAvg_engIcp = engIcpResults.slice(0, 5).reduce((s, r) => s + r.score, 0) / 5; 334 const engLeadAvg_engIcp = engIcpResults.slice(5, 10).reduce((s, r) => s + r.score, 0) / 5; 335 console.log(` Sales ICP: sales leads avg=${salesLeadAvg_salesIcp.toFixed(0)}, eng leads avg=${engLeadAvg_salesIcp.toFixed(0)}`); 336 console.log(` Eng ICP: sales leads avg=${salesLeadAvg_engIcp.toFixed(0)}, eng leads avg=${engLeadAvg_engIcp.toFixed(0)}`); 337 // With Engineering ICP, eng leads should score higher than with Sales ICP 338 // OR with Sales ICP, sales leads should score higher than eng leads 339 // At least one of these should be true — scores should shift with ICP 340 const engLeadsShifted = Math.abs(engLeadAvg_engIcp - engLeadAvg_salesIcp) >= 3; 341 const salesLeadsShifted = Math.abs(salesLeadAvg_salesIcp - salesLeadAvg_engIcp) >= 3; 342 assert(engLeadsShifted || salesLeadsShifted, 343 'Expected scores to shift meaningfully between different ICPs'); 344}); 345 346// --------------------------------------------------------------------------- 347// Test 6: Edge cases — sparse data 348// --------------------------------------------------------------------------- 349 350console.log('\nEdge Cases:'); 351 352await test('Lead with only email field gets scored', async () => { 353 const { datasetId } = await runTask({ 354 leads: [{ email: 'jane@example.com' }], 355 icp: ICP_SAAS_ENGINEERING, 356 }); 357 const results = await fetchDataset(datasetId); 358 assert(results.length === 1, `Expected 1 result, got ${results.length}`); 359 validateResult(results[0], 0); 360 assert(results[0].confidence < 0.7, `Expected low confidence for sparse data, got ${results[0].confidence}`); 361}); 362 363await test('Lead with only company name gets scored', async () => { 364 const { datasetId } = await runTask({ 365 leads: [{ company: 'Salesforce' }], 366 icp: ICP_SAAS_ENGINEERING, 367 }); 368 const results = await fetchDataset(datasetId); 369 assert(results.length === 1, `Expected 1 result, got ${results.length}`); 370 validateResult(results[0], 0); 371}); 372 373await test('Wrapped {input: {...}} format works', async () => { 374 const { datasetId } = await runTask({ 375 leads: [ 376 { input: { company: 'Acme Corp', title: 'VP Engineering', industry: 'SaaS' } }, 377 { input: { company: 'MegaRetail', title: 'Intern', industry: 'Retail' } }, 378 ], 379 icp: ICP_SAAS_ENGINEERING, 380 }); 381 const results = await fetchDataset(datasetId); 382 assert(results.length === 2, `Expected 2 results, got ${results.length}`); 383 results.forEach((r, i) => validateResult(r, i)); 384}); 385 386await test('Single lead via "lead" shorthand field', async () => { 387 // Override task's saved leads with empty array so only "lead" is scored 388 const { datasetId } = await runTask({ 389 lead: { company: 'DataFlow', title: 'CTO', industry: 'SaaS', employees: 200 }, 390 leads: [], 391 icp: ICP_SAAS_ENGINEERING, 392 }); 393 const results = await fetchDataset(datasetId); 394 assert(results.length === 1, `Expected 1 result, got ${results.length}`); 395 validateResult(results[0], 0); 396}); 397 398await test('Mixed lead + leads works (lead prepended)', async () => { 399 const { datasetId } = await runTask({ 400 lead: { company: 'FirstCo', title: 'CEO' }, 401 leads: [{ company: 'SecondCo', title: 'Intern' }], 402 icp: ICP_SAAS_ENGINEERING, 403 }); 404 const results = await fetchDataset(datasetId); 405 assert(results.length === 2, `Expected 2 results, got ${results.length}`); 406 assert(results[0].id === 1, 'First result should have id 1'); 407 assert(results[1].id === 2, 'Second result should have id 2'); 408 results.forEach((r, i) => validateResult(r, i)); 409}); 410 411// --------------------------------------------------------------------------- 412// Test 7: Full LinkedIn batch (all 78 leads) 413// --------------------------------------------------------------------------- 414 415console.log('\nFull LinkedIn Batch:'); 416 417if (!QUICK_MODE) { 418 let allLinkedinResults; 419 420 await test('All 78 LinkedIn leads scored successfully', async () => { 421 const { datasetId } = await runTask( 422 { leads: stripSource(linkedinLeads), icp: ICP_SAAS_ENGINEERING }, 423 180_000, // 3 min timeout for large batch 424 ); 425 allLinkedinResults = await fetchDataset(datasetId); 426 assert(allLinkedinResults.length === 78, `Expected 78 results, got ${allLinkedinResults.length}`); 427 allLinkedinResults.forEach((r, i) => validateResult(r, i)); 428 }); 429 430 await test('All leads have non-empty summaries', async () => { 431 assert(allLinkedinResults, 'No results'); 432 const emptySummaries = allLinkedinResults.filter((r) => !r.summary || r.summary.includes('Failed to parse')); 433 assert(emptySummaries.length === 0, `${emptySummaries.length} leads have empty/failed summaries`); 434 }); 435 436 await test('Confidence varies with data richness', async () => { 437 assert(allLinkedinResults, 'No results'); 438 const confidences = allLinkedinResults.map((r) => r.confidence); 439 const min = Math.min(...confidences); 440 const max = Math.max(...confidences); 441 console.log(` Confidence range: ${min.toFixed(2)}-${max.toFixed(2)}`); 442 // Leads have varying data richness (some have summaries, some don't) 443 assert(max - min >= 0.05, `Confidence spread too narrow: ${min.toFixed(2)}-${max.toFixed(2)}`); 444 }); 445 446 await test('Score distribution uses multiple bands', async () => { 447 assert(allLinkedinResults, 'No results'); 448 const bands = new Set(allLinkedinResults.map((r) => r.band)); 449 const scores = allLinkedinResults.map((r) => r.score); 450 const bandCounts = {}; 451 allLinkedinResults.forEach((r) => { bandCounts[r.band] = (bandCounts[r.band] || 0) + 1; }); 452 console.log(` Bands: ${Object.entries(bandCounts).map(([b, c]) => `${b}=${c}`).join(', ')}`); 453 console.log(` Score range: ${Math.min(...scores)}-${Math.max(...scores)}, avg: ${(scores.reduce((a, b) => a + b, 0) / scores.length).toFixed(0)}`); 454 // Real data may not cover all 4 bands — depends on ICP specificity vs data richness 455 assert(bands.size >= 2, `Expected at least 2 bands in 78 results, got ${bands.size}: ${[...bands].join(', ')}`); 456 }); 457 458 await test('Misc leads (household CEO) score poorly for SaaS ICP', async () => { 459 assert(allLinkedinResults, 'No results'); 460 // Misc leads are at indices 75-77 (eng: 0-24, sales: 25-49, full: 50-74, misc: 75-77) 461 const miscResults = allLinkedinResults.slice(75, 78); 462 const miscAvg = miscResults.reduce((s, r) => s + r.score, 0) / miscResults.length; 463 console.log(` Misc leads avg: ${miscAvg.toFixed(0)} (${miscResults.map((r) => r.score).join(', ')})`); 464 assert(miscAvg < 50, `Misc leads avg (${miscAvg.toFixed(0)}) should be below 50 for SaaS ICP`); 465 }); 466} else { 467 skipTest('All 78 LinkedIn leads scored successfully', 'quick mode'); 468 skipTest('All leads have non-empty summaries', 'quick mode'); 469 skipTest('Confidence varies with data richness', 'quick mode'); 470 skipTest('Score distribution has all four bands', 'quick mode'); 471 skipTest('Misc leads (household CEO) score poorly for SaaS ICP', 'quick mode'); 472} 473 474// --------------------------------------------------------------------------- 475// Test 8: Nested array flattening 476// --------------------------------------------------------------------------- 477 478console.log('\nNested Array Handling:'); 479 480await test('Nested array [[{...}, {...}]] is flattened to 2 leads', async () => { 481 const { datasetId } = await runTask({ 482 leads: [[ 483 { company: 'NestedCo', title: 'CEO', industry: 'SaaS' }, 484 { company: 'NestedTwo', title: 'CTO', industry: 'FinTech' }, 485 ]], 486 icp: ICP_SAAS_ENGINEERING, 487 }); 488 const results = await fetchDataset(datasetId); 489 assert(results.length === 2, `Expected 2 results from nested array, got ${results.length}`); 490 results.forEach((r, i) => validateResult(r, i)); 491 assert(results[0].input.company === 'NestedCo', `First lead should be NestedCo, got ${results[0].input.company}`); 492 assert(results[1].input.company === 'NestedTwo', `Second lead should be NestedTwo, got ${results[1].input.company}`); 493}); 494 495await test('Mixed nested + flat leads', async () => { 496 const { datasetId } = await runTask({ 497 leads: [ 498 { company: 'FlatCo', title: 'VP Engineering' }, 499 [{ company: 'InnerA', title: 'Director' }, { company: 'InnerB', title: 'Manager' }], 500 { company: 'FlatTwo', title: 'CTO' }, 501 ], 502 icp: ICP_SAAS_ENGINEERING, 503 }); 504 const results = await fetchDataset(datasetId); 505 assert(results.length === 4, `Expected 4 results from mixed input, got ${results.length}`); 506 results.forEach((r, i) => validateResult(r, i)); 507 assert(results[0].input.company === 'FlatCo', 'First should be FlatCo'); 508 assert(results[1].input.company === 'InnerA', 'Second should be InnerA'); 509 assert(results[2].input.company === 'InnerB', 'Third should be InnerB'); 510 assert(results[3].input.company === 'FlatTwo', 'Fourth should be FlatTwo'); 511}); 512 513// --------------------------------------------------------------------------- 514// Test 9: Large/noisy lead distillation 515// --------------------------------------------------------------------------- 516 517console.log('\nLead Distillation:'); 518 519await test('Lead with 50+ noisy fields scored successfully, original preserved', async () => { 520 // Simulate a CRM export with lots of noise fields 521 const noisyLead = { 522 firstName: 'Jane', 523 lastName: 'Smith', 524 title: 'VP of Engineering', 525 company: 'Acme SaaS', 526 industry: 'Software', 527 employees: 200, 528 headline: 'Engineering leader focused on cloud platforms', 529 summary: 'Over 15 years of experience building SaaS platforms at scale. Led teams of 50+ engineers.', 530 location: 'San Francisco, CA', 531 connections: 500, 532 // Noise fields that should be filtered for the prompt 533 _id: '507f1f77bcf86cd799439011', 534 created_at: '2024-01-15T10:30:00Z', 535 updated_at: '2024-12-01T08:00:00Z', 536 last_activity_at: '2025-01-10T14:22:00Z', 537 avatar_url: 'https://cdn.example.com/photos/jsmith_200x200.jpg', 538 profile_url: 'https://linkedin.com/in/janesmith', 539 linkedin_url: 'https://linkedin.com/in/janesmith', 540 twitter_url: 'https://twitter.com/janesmith', 541 original_first_name: 'JANE', 542 original_last_name: 'SMITH', 543 custom_field_1: 'imported', 544 custom_field_2: 'segment_a', 545 crm_owner_id: 'usr_abc123', 546 crm_pipeline_stage: 'qualified', 547 salesforce_id: 'sf_00Q1234567', 548 hubspot_contact_id: 'hs_987654', 549 message_thread_count: 3, 550 conversation_id: 'conv_xyz789', 551 internal_score: 42, 552 meta_import_batch: 'batch_2024_q4', 553 source_campaign: 'linkedin_outreach_dec', 554 provider_id: 'prov_001', 555 third_party_email_verified: true, 556 import_date: '2024-11-30', 557 organization_id_1: 'org_001', 558 organization_start_date_1: '2020-03-01', 559 organization_end_date_1: '', 560 organization_id_2: 'org_002', 561 organization_start_date_2: '2015-06-01', 562 organization_end_date_2: '2020-02-28', 563 position_is_default_1: true, 564 position_description_1: 'Leading the platform engineering team', 565 position_is_default_2: false, 566 position_description_2: 'Senior engineer on the data team', 567 tmp_merge_key: 'jsmith_acme', 568 raw_import_data: '{"source":"linkedin","batch":42}', 569 // More padding to push over distill threshold 570 education: 'Stanford University, MS Computer Science', 571 skills: 'Python, Go, Kubernetes, AWS, Team Leadership', 572 organization_1: 'Acme SaaS (VP Engineering)', 573 organization_2: 'PreviousCorp (Director of Engineering)', 574 organization_3: 'StartupXYZ (Senior Engineer)', 575 email: 'jane@acmesaas.com', 576 phone: '+1-415-555-0123', 577 }; 578 const fieldCount = Object.keys(noisyLead).length; 579 assert(fieldCount >= 50, `Test lead should have 50+ fields, got ${fieldCount}`); 580 581 const { datasetId } = await runTask({ 582 leads: [noisyLead], 583 icp: ICP_SAAS_ENGINEERING, 584 }); 585 const results = await fetchDataset(datasetId); 586 assert(results.length === 1, `Expected 1 result, got ${results.length}`); 587 validateResult(results[0], 0); 588 589 // Original lead preserved in output (all fields present) 590 const outputInput = results[0].input; 591 assert(outputInput._id === '507f1f77bcf86cd799439011', 'Original noise field _id should be preserved in output'); 592 assert(outputInput.avatar_url === noisyLead.avatar_url, 'Original avatar_url should be preserved in output'); 593 assert(Object.keys(outputInput).length === fieldCount, `Output should preserve all ${fieldCount} fields, got ${Object.keys(outputInput).length}`); 594 595 // Should score well — VP Engineering at SaaS company 596 assert(results[0].score >= 50, `Expected decent score for VP Eng at SaaS, got ${results[0].score}`); 597}); 598 599// =================================================================== 600// Report 601// =================================================================== 602 603console.log(`\n=== Batch Test Results ===`); 604console.log(`Passed: ${passed}, Failed: ${failed}, Skipped: ${skipped}`); 605if (failures.length > 0) { 606 console.log('\nFailures:'); 607 for (const f of failures) { 608 console.log(` ${f.name}: ${f.error}`); 609 } 610} 611const result = failed === 0 ? (skipped > 0 ? 'PASS (with skips)' : 'PASS') : 'FAIL'; 612console.log(`\nRESULT: ${result}`); 613process.exit(failed === 0 ? 0 : 1);

1/** 2 * LLM-based lead scoring against an Ideal Customer Profile using OpenRouter. 3 * @see https://apify.com/apify/openrouter 4 */ 5 6import { Actor, log } from 'apify'; 7import OpenAI from 'openai'; 8 9const BATCH_SIZE = 10; 10const MAX_RETRIES = 3; 11const INITIAL_RETRY_DELAY_MS = 1000; 12const DEFAULT_CONCURRENCY = 5; 13const LARGE_REQUEST_THRESHOLD = 100; 14const LARGE_REQUEST_CONCURRENCY = 10; 15const MAX_TOKENS = 2048; 16const DISTILL_THRESHOLD_BYTES = 1500; 17const MAX_DISTILLED_FIELDS = 30; 18const MAX_FIELD_LENGTH = 500; 19const MAX_413_SPLIT_DEPTH = 3; 20 21const OPENROUTER_BASE_URL = 'https://openrouter.apify.actor/api/v1'; 22const OPENROUTER_DIRECT_URL = 'https://openrouter.ai/api/v1'; 23 24/** 25 * Convert a numeric score (0-100) to a band label. 26 */ 27export function scoreToBand(score) { 28 if (score >= 80) return 'excellent'; 29 if (score >= 60) return 'good'; 30 if (score >= 40) return 'fair'; 31 return 'poor'; 32} 33 34/** 35 * Build the system prompt for ICP scoring. 36 */ 37function buildSystemPrompt(icp) { 38 return `You are scoring sales leads against an Ideal Customer Profile (ICP). 39 40ICP DESCRIPTION: 41${icp} 42 43SCORING SCALE (0-100): 44- 90-100: Perfect fit — matches all major ICP criteria 45- 70-89: Strong fit — matches most criteria, minor gaps 46- 50-69: Moderate fit — some criteria match, notable gaps 47- 30-49: Weak fit — few matching criteria 48- 0-29: Poor fit — does not match the ICP 49 50Score based on ALL available fields. If a lead has limited data, lower your confidence (not the score) — score what you can see. 51 52CONFIDENCE (0-1): 53- 0.9-1.0: Lead has rich data covering most ICP dimensions 54- 0.7-0.89: Lead has adequate data for reasonable scoring 55- 0.5-0.69: Lead has sparse data, scoring is best-guess 56- Below 0.5: Lead has minimal data, score is unreliable 57 58OUTPUT FORMAT (strict JSON, no comments): 59[{"index": 0, "score": 85, "summary": "Strong fit: VP-level at mid-size SaaS company.", "confidence": 0.9}] 60Return ONLY the JSON array with objects containing "index", "score", "summary", and "confidence" keys.`; 61} 62 63/** 64 * Noise field patterns — fields that add bulk without ICP-relevant signal. 65 * Blacklist approach: drop noise, keep everything else. 66 */ 67const NOISE_PATTERNS = [ 68 /^(id|_id|uid|uuid|key|hash|urn|slug)$/i, 69 /(_id|_key|_hash|_urn|_slug|_token)$/i, 70 /^(created|updated|modified|deleted|last_seen|last_activity|synced)(_at|_date|_time|_on)?$/i, 71 /(timestamp|_ts|_epoch)$/i, 72 /(avatar|photo|image|picture|icon|thumbnail|logo)(_url)?$/i, 73 /^(profile_url|linkedin_url|facebook_url|twitter_url|github_url|website_url|company_url)$/i, 74 /^(message|msg|note|comment|conversation|thread|chat)/i, 75 /^(original_|custom_|internal_|meta_|raw_|tmp_|temp_)/i, 76 /^(crm_|sf_|hubspot_|salesforce_|pipedrive_|zoho_)/i, 77 /^organization_(id|start_date|end_date)_\d+$/i, 78 /^position_(is_default|description)_\d+$/i, 79 /^(third_party_|provider_|source_|import_)/i, 80 /^[a-f0-9]{24,}$/i, // hex hash keys (MongoDB ObjectIds, etc.) 81]; 82 83/** 84 * Truncate a string value to max length. 85 */ 86function truncateValue(value, maxLen = MAX_FIELD_LENGTH) { 87 if (typeof value !== 'string' || value.length <= maxLen) return value; 88 return `${value.slice(0, maxLen)}...`; 89} 90 91/** 92 * Distill a lead object for LLM prompt — drops noise fields, empty values, 93 * and truncates long strings. Only affects the prompt, not the stored output. 94 */ 95function distillLead(lead) { 96 const raw = JSON.stringify(lead); 97 if (raw.length <= DISTILL_THRESHOLD_BYTES) return lead; 98 99 const distilled = {}; 100 let fieldCount = 0; 101 102 for (const [key, value] of Object.entries(lead)) { 103 if (fieldCount >= MAX_DISTILLED_FIELDS) break; 104 105 // Drop empty/null/undefined 106 if (value === null || value === undefined || value === '') continue; 107 108 // Drop noise fields 109 if (NOISE_PATTERNS.some((pattern) => pattern.test(key))) continue; 110 111 distilled[key] = truncateValue(value); 112 fieldCount++; 113 } 114 115 return distilled; 116} 117 118/** 119 * Build the user prompt for a batch of leads. 120 * Applies distillation to reduce prompt size for large/noisy leads. 121 */ 122function buildPrompt(leads) { 123 const leadList = leads.map((lead, i) => `${i}. ${JSON.stringify(distillLead(lead))}`).join('\n'); 124 125 return `Score the following ${leads.length} leads against the ICP. 126 127${leadList}`; 128} 129 130/** 131 * Attempt to repair truncated JSON arrays. 132 */ 133function repairTruncatedJson(jsonStr) { 134 try { 135 JSON.parse(jsonStr); 136 return jsonStr; 137 } catch { 138 // Continue with repair 139 } 140 141 if (!jsonStr.trimStart().startsWith('[')) { 142 return jsonStr; 143 } 144 145 let lastValidEnd = -1; 146 147 const lastCommaObj = jsonStr.lastIndexOf('},'); 148 if (lastCommaObj > 0) { 149 lastValidEnd = lastCommaObj + 1; 150 } 151 152 const lastBrace = jsonStr.lastIndexOf('}'); 153 if (lastBrace > lastValidEnd) { 154 const afterBrace = jsonStr.slice(lastBrace + 1).trim(); 155 if (afterBrace === '' || afterBrace === ']' || afterBrace.startsWith(',') || afterBrace.startsWith(']')) { 156 lastValidEnd = lastBrace; 157 } 158 } 159 160 if (lastValidEnd > 0) { 161 const repaired = `${jsonStr.slice(0, lastValidEnd + 1)}]`; 162 try { 163 JSON.parse(repaired); 164 log.debug('Repaired truncated JSON response', { 165 originalLength: jsonStr.length, 166 repairedLength: repaired.length, 167 }); 168 return repaired; 169 } catch { 170 // Repair failed 171 } 172 } 173 174 return jsonStr; 175} 176 177/** 178 * Parse the LLM response and map results back to original leads. 179 */ 180function parseResponse(content, leads) { 181 try { 182 let jsonStr = content.trim(); 183 if (jsonStr.includes('```')) { 184 jsonStr = jsonStr.replace(/```json?\n?/g, '').replace(/```/g, '').trim(); 185 } 186 187 // Strip comments 188 jsonStr = jsonStr.replace(/\/\/[^\n]*/g, ''); 189 jsonStr = jsonStr.replace(/\/\*[\s\S]*?\*\//g, ''); 190 191 jsonStr = repairTruncatedJson(jsonStr); 192 193 const parsed = JSON.parse(jsonStr); 194 195 if (!Array.isArray(parsed)) { 196 throw new Error('Response is not an array'); 197 } 198 199 return leads.map((lead, i) => { 200 const result = parsed.find((r) => r.index === i); 201 if (result) { 202 return { 203 score: clampScore(result.score), 204 summary: result.summary || '', 205 confidence: clampConfidence(result.confidence), 206 }; 207 } 208 return { 209 score: 50, 210 summary: 'Lead not found in LLM response', 211 confidence: 0.3, 212 }; 213 }); 214 } catch (error) { 215 log.warning('Failed to parse LLM response', { error: error.message, content: content.slice(0, 200) }); 216 217 return leads.map(() => ({ 218 score: 50, 219 summary: `Failed to parse LLM response: ${error.message}`, 220 confidence: 0.3, 221 })); 222 } 223} 224 225function clampScore(value) { 226 if (typeof value !== 'number' || Number.isNaN(value)) return 50; 227 return Math.max(0, Math.min(100, Math.round(value))); 228} 229 230function clampConfidence(value) { 231 if (typeof value !== 'number' || Number.isNaN(value)) return 0.5; 232 return Math.max(0, Math.min(1, value)); 233} 234 235function sleep(ms) { 236 return new Promise((resolve) => { 237 setTimeout(resolve, ms); 238 }); 239} 240 241function is413Error(error) { 242 if (error.status === 413) return true; 243 if (error.message?.includes('413') || error.message?.toLowerCase().includes('payload too large')) return true; 244 return false; 245} 246 247function isRetryableError(error) { 248 if (is413Error(error)) return false; // 413 needs splitting, not retrying 249 if (error.retryable) return true; 250 if (error.code === 'ECONNRESET' || error.code === 'ETIMEDOUT' || error.code === 'ENOTFOUND') { 251 return true; 252 } 253 if (error.status === 429 || error.status >= 500) { 254 return true; 255 } 256 if (error.message?.includes('timeout') || error.message?.includes('network')) { 257 return true; 258 } 259 return false; 260} 261 262/** 263 * Score a batch of leads with a single LLM call. 264 * On 413 (payload too large), recursively splits the batch in half. 265 */ 266async function scoreBatch(openai, model, systemPrompt, leads, splitDepth = 0) { 267 const prompt = buildPrompt(leads); 268 let lastError; 269 270 for (let attempt = 1; attempt <= MAX_RETRIES; attempt++) { 271 try { 272 const completion = await openai.chat.completions.create({ 273 model, 274 messages: [ 275 { role: 'system', content: systemPrompt }, 276 { role: 'user', content: prompt }, 277 ], 278 temperature: 0.3, 279 max_tokens: MAX_TOKENS, 280 timeout: 60000, 281 }); 282 283 const responseContent = completion.choices[0]?.message?.content; 284 if (!responseContent) { 285 const emptyErr = new Error('Empty response from LLM'); 286 emptyErr.retryable = true; 287 throw emptyErr; 288 } 289 290 return parseResponse(responseContent, leads); 291 } catch (error) { 292 lastError = error; 293 294 // Handle 413 by splitting the batch 295 if (is413Error(error)) { 296 if (leads.length <= 1 || splitDepth >= MAX_413_SPLIT_DEPTH) { 297 log.error('Lead too large for LLM even after distillation', { 298 leadFields: Object.keys(leads[0] || {}).length, 299 promptLength: prompt.length, 300 }); 301 return leads.map(() => ({ 302 score: 0, 303 summary: 'Lead data too large to score. Try reducing the number of fields per lead.', 304 confidence: 0, 305 })); 306 } 307 308 const mid = Math.ceil(leads.length / 2); 309 log.warning(`413 payload too large — splitting batch of ${leads.length} (depth ${splitDepth + 1})`, { 310 promptLength: prompt.length, 311 }); 312 const [left, right] = await Promise.all([ 313 scoreBatch(openai, model, systemPrompt, leads.slice(0, mid), splitDepth + 1), 314 scoreBatch(openai, model, systemPrompt, leads.slice(mid), splitDepth + 1), 315 ]); 316 return [...left, ...right]; 317 } 318 319 if (attempt < MAX_RETRIES && isRetryableError(error)) { 320 const delayMs = INITIAL_RETRY_DELAY_MS * (2 ** (attempt - 1)); 321 log.warning(`LLM request failed (attempt ${attempt}/${MAX_RETRIES}), retrying in ${delayMs}ms...`, { 322 error: error.message, 323 }); 324 await sleep(delayMs); 325 } else if (attempt < MAX_RETRIES) { 326 log.error('LLM request failed with non-retryable error', { error: error.message }); 327 break; 328 } 329 } 330 } 331 332 const errorMessage = lastError?.message || 'Unknown error'; 333 log.error('LLM request failed after all retries', { error: errorMessage }); 334 await Actor.fail(`LLM service unavailable: ${errorMessage}. Please try again later or contact the developer.`); 335} 336 337/** 338 * Create a scorer instance configured with OpenRouter. 339 * @param {string} model - OpenRouter model to use 340 * @param {string} icp - Ideal Customer Profile description 341 * @param {string|null} openRouterApiKey - Optional BYOK key 342 * @returns {Object} Scorer with score() method 343 */ 344export function createScorer(model, icp, openRouterApiKey = null) { 345 let openai; 346 347 if (openRouterApiKey) { 348 log.info('Using direct OpenRouter API (bring your own key)'); 349 openai = new OpenAI({ 350 baseURL: OPENROUTER_DIRECT_URL, 351 apiKey: openRouterApiKey, 352 timeout: 120_000, 353 }); 354 } else { 355 const apifyToken = process.env.APIFY_TOKEN; 356 if (!apifyToken) { 357 throw new Error('APIFY_TOKEN environment variable is required for OpenRouter access'); 358 } 359 openai = new OpenAI({ 360 baseURL: OPENROUTER_BASE_URL, 361 apiKey: 'apify-openrouter', 362 timeout: 120_000, 363 defaultHeaders: { 364 Authorization: `Bearer ${apifyToken}`, 365 }, 366 }); 367 } 368 369 const systemPrompt = buildSystemPrompt(icp); 370 371 return { 372 /** 373 * Score an array of lead objects against the ICP. 374 * @param {Array<Object>} leads - Lead objects to score 375 * @returns {Promise<Array>} Array of {score, summary, confidence} results 376 */ 377 async score(leads) { 378 const batches = []; 379 for (let i = 0; i < leads.length; i += BATCH_SIZE) { 380 batches.push({ 381 leads: leads.slice(i, i + BATCH_SIZE), 382 startIndex: i, 383 }); 384 } 385 386 const totalBatches = batches.length; 387 const concurrency = leads.length >= LARGE_REQUEST_THRESHOLD 388 ? LARGE_REQUEST_CONCURRENCY 389 : DEFAULT_CONCURRENCY; 390 391 log.info(`Scoring ${leads.length} leads in ${totalBatches} batches (concurrency: ${concurrency})`); 392 393 const results = new Array(leads.length); 394 for (let i = 0; i < batches.length; i += concurrency) { 395 const chunk = batches.slice(i, i + concurrency); 396 const chunkStart = i + 1; 397 const chunkEnd = Math.min(i + concurrency, totalBatches); 398 399 log.info(`Processing batches ${chunkStart}-${chunkEnd}/${totalBatches}`); 400 401 const chunkResults = await Promise.all( 402 chunk.map((batch) => scoreBatch(openai, model, systemPrompt, batch.leads)), 403 ); 404 405 chunk.forEach((batch, idx) => { 406 const batchResults = chunkResults[idx]; 407 batchResults.forEach((result, resultIdx) => { 408 results[batch.startIndex + resultIdx] = result; 409 }); 410 }); 411 } 412 413 return results; 414 }, 415 }; 416}

1/** 2 * Superlead ICP Scorer 3 * 4 * Score leads against your Ideal Customer Profile using AI. 5 * Returns fit scores (0-100), band labels, and plain-English explanations. 6 */ 7 8import http from 'node:http'; 9import { Actor, log } from 'apify'; 10 11import { createScorer, scoreToBand } from './scorer.js'; 12 13const PPE_EVENT = 'icp-score'; 14 15/** 16 * Normalize flexible lead input formats. 17 * Accepts: [{...}], [{input: {...}}], or [[{...}, {...}]] (nested arrays flattened one level) 18 * Returns: [{...}] 19 */ 20function normalizeLeads(leads) { 21 return leads.flatMap((lead) => { 22 if (Array.isArray(lead)) { 23 log.warning(`Flattening nested array of ${lead.length} leads`); 24 return lead.filter((item) => item && typeof item === 'object' && !Array.isArray(item)); 25 } 26 if (lead && typeof lead === 'object' && 'input' in lead && typeof lead.input === 'object') { 27 return lead.input; 28 } 29 if (lead && typeof lead === 'object') return lead; 30 return []; 31 }).filter(Boolean); 32} 33 34/** 35 * Auto-generate a human-readable label from a lead's fields. 36 */ 37function generateLabel(lead) { 38 const name = lead.name || lead.fullName || [lead.firstName, lead.lastName].filter(Boolean).join(' ') || null; 39 const title = lead.title || lead.jobTitle || lead.position || null; 40 const company = lead.company || lead.companyName || lead.organization || null; 41 42 const parts = []; 43 if (name && title) { 44 parts.push(`${name}, ${title}`); 45 } else if (name || title) { 46 parts.push(name || title); 47 } 48 if (company) { 49 parts.push(parts.length > 0 ? `at ${company}` : company); 50 } 51 return parts.join(' ') || JSON.stringify(lead).slice(0, 80); 52} 53 54await Actor.init(); 55 56if (Actor.config.get('metaOrigin') === 'STANDBY') { 57 startStandbyServer(); 58} else { 59 await runBatchMode(); 60 await Actor.exit(); 61} 62 63// --------------------------------------------------------------------------- 64// Standby mode — HTTP server for instant single-lead scoring 65// --------------------------------------------------------------------------- 66 67function startStandbyServer() { 68 const port = Actor.config.get('containerPort'); 69 70 const server = http.createServer(async (req, res) => { 71 if (req.headers['x-apify-container-server-readiness-probe']) { 72 res.writeHead(200, { 'Content-Type': 'application/json' }); 73 res.end(JSON.stringify({ status: 'ready' })); 74 return; 75 } 76 77 if (req.method !== 'GET') { 78 res.writeHead(405, { 'Content-Type': 'application/json' }); 79 res.end(JSON.stringify({ error: 'Method not allowed. Use GET.' })); 80 return; 81 } 82 83 const reqUrl = new URL(req.url, `http://${req.headers.host}`); 84 if (!reqUrl.searchParams.get('lead') && !reqUrl.searchParams.get('icp')) { 85 res.writeHead(200, { 'Content-Type': 'text/html' }); 86 res.end(getLandingPageHtml()); 87 return; 88 } 89 90 try { 91 const result = await handleStandbyRequest(reqUrl, req); 92 await Actor.pushData(result); 93 94 // Charge PPE 95 try { 96 await Actor.charge({ eventName: PPE_EVENT, count: 1 }); 97 } catch (chargeErr) { 98 console.warn(`PPE charge failed: ${chargeErr.message}`); 99 } 100 101 res.writeHead(200, { 'Content-Type': 'application/json' }); 102 res.end(JSON.stringify(result)); 103 } catch (err) { 104 const statusCode = err.statusCode || 500; 105 res.writeHead(statusCode, { 'Content-Type': 'application/json' }); 106 res.end(JSON.stringify({ error: err.message })); 107 } 108 }); 109 110 server.listen(port, () => { 111 console.log(`Superlead ICP Scorer Standby server listening on port ${port}`); 112 }); 113} 114 115async function handleStandbyRequest(reqUrl, req) { 116 const leadParam = reqUrl.searchParams.get('lead'); 117 const icp = reqUrl.searchParams.get('icp'); 118 119 if (!leadParam) { 120 const err = new Error("Provide a 'lead' query parameter with the lead object as JSON."); 121 err.statusCode = 400; 122 throw err; 123 } 124 125 if (!icp) { 126 const err = new Error("Provide an 'icp' query parameter with your Ideal Customer Profile description."); 127 err.statusCode = 400; 128 throw err; 129 } 130 131 let lead; 132 try { 133 lead = JSON.parse(leadParam); 134 } catch { 135 const err = new Error("Invalid JSON in 'lead' parameter. Provide a valid JSON object."); 136 err.statusCode = 400; 137 throw err; 138 } 139 140 if (!lead || typeof lead !== 'object' || Array.isArray(lead)) { 141 const err = new Error("'lead' must be a JSON object (not an array or primitive)."); 142 err.statusCode = 400; 143 throw err; 144 } 145 146 const model = reqUrl.searchParams.get('model') || 'openrouter/auto'; 147 const openRouterApiKey = req.headers['x-openrouter-key'] || null; 148 149 const scorer = createScorer(model, icp, openRouterApiKey); 150 const results = await scorer.score([lead]); 151 152 if (results.length === 0) { 153 return { id: 1, label: generateLabel(lead), score: 50, band: 'fair', summary: 'Unable to score lead.', confidence: 0 }; 154 } 155 156 const r = results[0]; 157 return { 158 id: 1, 159 input: lead, 160 label: generateLabel(lead), 161 score: r.score, 162 band: scoreToBand(r.score), 163 summary: r.summary, 164 confidence: Math.round(r.confidence * 100) / 100, 165 }; 166} 167 168// --------------------------------------------------------------------------- 169// Batch mode — score multiple leads in a standard Actor run 170// --------------------------------------------------------------------------- 171 172async function runBatchMode() { 173 const input = await Actor.getInput(); 174 let { leads: rawLeads, lead, icp } = input || {}; 175 176 // Support single "lead" object for API/integration callers 177 if (lead && typeof lead === 'object' && !Array.isArray(lead)) { 178 if (!Array.isArray(rawLeads)) rawLeads = []; 179 rawLeads = [lead, ...rawLeads]; 180 } 181 182 // Validate ICP 183 if (!icp || typeof icp !== 'string' || !icp.trim()) { 184 await Actor.fail('Missing or invalid "icp" field. Provide a string describing your Ideal Customer Profile, e.g. "B2B SaaS companies with 50-500 employees".'); 185 return; 186 } 187 188 // Validate leads 189 if (!rawLeads || !Array.isArray(rawLeads) || rawLeads.length === 0) { 190 await Actor.fail('Missing or invalid "leads" field. Provide an array of lead objects, e.g. [{"company": "Acme Corp", "title": "VP of Engineering"}]. You can also pass a single lead via the "lead" field.'); 191 return; 192 } 193 194 const model = input.model ?? 'openrouter/auto'; 195 const openRouterApiKey = input.openRouterApiKey ?? null; 196 197 // Normalize input format 198 const leads = normalizeLeads(rawLeads); 199 200 if (leads.length === 0) { 201 await Actor.fail('No valid lead objects found after input normalization. Each item in "leads" must be a JSON object, e.g. [{"company": "Acme Corp", "title": "VP of Engineering"}].'); 202 return; 203 } 204 205 if (leads.length > 5000) { 206 await Actor.fail(`Too many leads (${leads.length}). Maximum is 5,000 per run. Split your data into smaller batches.`); 207 return; 208 } 209 210 if (leads.length > 500) { 211 log.warning(`Large batch of ${leads.length} leads — this may take several minutes.`); 212 } 213 214 log.info(`Starting ICP scoring of ${leads.length} leads`, { model }); 215 216 // Score leads 217 const scorer = createScorer(model, icp.trim(), openRouterApiKey); 218 const scoreResults = await scorer.score(leads); 219 220 // Build output 221 const results = leads.map((lead, i) => { 222 const r = scoreResults[i]; 223 return { 224 id: i + 1, 225 input: lead, 226 label: generateLabel(lead), 227 score: r.score, 228 band: scoreToBand(r.score), 229 summary: r.summary, 230 confidence: Math.round(r.confidence * 100) / 100, 231 }; 232 }); 233 234 // Push to dataset and charge PPE per item 235 let chargeLimitReached = false; 236 let chargedCount = 0; 237 for (const result of results) { 238 await Actor.pushData(result); 239 if (!chargeLimitReached) { 240 try { 241 const chargeResult = await Actor.charge({ eventName: PPE_EVENT, count: 1 }); 242 chargedCount++; 243 if (chargeResult?.eventChargeLimitReached) { 244 chargeLimitReached = true; 245 log.warning(`User spending limit reached after ${chargedCount}/${results.length} leads. Remaining leads scored but not charged.`); 246 } 247 } catch (chargeErr) { 248 console.warn(`PPE charge failed: ${chargeErr.message}`); 249 } 250 } 251 } 252 253 // Log summary 254 const avgScore = Math.round(results.reduce((sum, r) => sum + r.score, 0) / results.length); 255 const bandCounts = results.reduce((acc, r) => { acc[r.band] = (acc[r.band] || 0) + 1; return acc; }, {}); 256 257 log.info('Scoring complete', { 258 totalLeads: results.length, 259 charged: chargedCount, 260 averageScore: avgScore, 261 bands: bandCounts, 262 }); 263} 264 265// --------------------------------------------------------------------------- 266// Landing page HTML for Standby mode 267// --------------------------------------------------------------------------- 268 269function getLandingPageHtml() { 270 return `<!DOCTYPE html> 271<html lang="en"> 272<head> 273<meta charset="utf-8"> 274<meta name="viewport" content="width=device-width, initial-scale=1"> 275<title>Superlead ICP Scorer — Superlative</title> 276<link rel="preconnect" href="https://fonts.googleapis.com"> 277<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin> 278<link href="https://fonts.googleapis.com/css2?family=DM+Sans:wght@400;500;700&family=Space+Mono:wght@400;700&display=swap" rel="stylesheet"> 279<style> 280:root{--color-bg:#0a0e14;--color-surface:#12171f;--color-border:#1e2632;--color-text:#e8eaed;--color-text-muted:#8b95a5;--color-accent:#60a5fa;--color-accent-dim:rgba(96,165,250,0.15);--font-display:'Space Mono',monospace;--font-body:'DM Sans',sans-serif} 281*{margin:0;padding:0;box-sizing:border-box} 282body{font-family:var(--font-body);background:var(--color-bg);color:var(--color-text);line-height:1.6;min-height:100vh;overflow-x:hidden} 283a{color:var(--color-accent);text-decoration:none;transition:color .2s ease} 284a:hover{color:#93c5fd} 285.grid-bg{position:fixed;top:0;left:0;width:100%;height:100%;background-image:linear-gradient(var(--color-border) 1px,transparent 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320.product-card:hover{border-color:var(--color-accent);transform:translateY(-2px)} 321.product-name{font-family:var(--font-display);font-size:14px;font-weight:700;margin-bottom:8px;color:var(--color-text);display:flex;align-items:center;gap:8px} 322.product-name .status{font-size:9px;font-weight:400;padding:3px 6px;background:var(--color-accent-dim);color:var(--color-accent);letter-spacing:.1em} 323.product-desc{font-size:14px;color:var(--color-text-muted);line-height:1.5} 324footer{padding:48px 0;border-top:1px solid var(--color-border)} 325.footer-content{display:flex;justify-content:space-between;align-items:center;flex-wrap:wrap;gap:24px} 326.footer-text{font-size:13px;color:var(--color-text-muted)} 327.footer-links{display:flex;gap:24px} 328.footer-links a{font-family:var(--font-display);font-size:12px;color:var(--color-text-muted);letter-spacing:.05em} 329.footer-links a:hover{color:var(--color-accent)} 330@media(max-width:600px){.hero{padding:60px 0 40px}.section{padding:40px 0}.footer-content{flex-direction:column;align-items:flex-start}pre{font-size:12px;padding:12px 14px}} 331</style> 332</head> 333<body> 334<div class="grid-bg"></div> 335<div class="accent-line"></div> 336 337<div class="container"> 338 <header> 339 <a href="https://apify.com/superlativetech?fpr=8e9l1" class="logo"> 340 <div class="logo-mark"> 341 <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2.5"> 342 <polyline points="4 17 10 11 4 5"></polyline> 343 <line x1="12" y1="19" x2="20" y2="19"></line> 344 </svg> 345 </div> 346 Superlative 347 </a> 348 </header> 349 350 <section class="hero"> 351 <div class="hero-label">Superlead</div> 352 <h1>ICP <span class="highlight">Scorer</span></h1> 353 <p class="hero-desc">AI-powered lead scoring against your Ideal Customer Profile. Get fit scores, band labels, and plain-English explanations for every lead. Sub-second responses via Standby API.</p> 354 <a href="https://apify.com/superlativetech/superlead-icp-scorer?fpr=8e9l1" class="hero-link">View on Apify Store →</a> 355 </section> 356 357 <section class="section"> 358 <div class="section-label">Features</div> 359 <h2>What this does</h2> 360 <ul> 361 <li><strong>AI-powered scoring</strong> — LLM evaluates every lead against your ICP description</li> 362 <li><strong>Fit scores (0-100)</strong> — Excellent, good, fair, or poor band labels</li> 363 <li><strong>Plain-English summaries</strong> — Explains why each lead scored the way it did</li> 364 <li><strong>Any lead format</strong> — Works with any JSON fields (company, title, industry, etc.)</li> 365 <li><strong>BYOK support</strong> — Use your own OpenRouter API key via header</li> 366 <li><strong>Batch mode</strong> — Score hundreds of leads via the standard Actor run</li> 367 </ul> 368 </section> 369 370 <section class="section"> 371 <div class="section-label">Getting Started</div> 372 <h2>Quick start</h2> 373 <p>Replace <code>YOUR_TOKEN</code> with your Apify API token.</p> 374 375 <p style="margin-top:16px"><strong>Score a single lead:</strong></p> 376 <pre>curl "https://superlativetech--superlead-icp-scorer.apify.actor?token=YOUR_TOKEN&lead=%7B%22company%22%3A%22Acme%22%2C%22title%22%3A%22VP+Engineering%22%7D&icp=B2B+SaaS+50-500+employees"</pre> 377 378 <p><strong>With your own OpenRouter key:</strong></p> 379 <pre>curl -H "X-OpenRouter-Key: sk-or-..." "https://superlativetech--superlead-icp-scorer.apify.actor?token=YOUR_TOKEN&lead=%7B%22company%22%3A%22Acme%22%7D&icp=B2B+SaaS"</pre> 380 </section> 381 382 <section class="section"> 383 <div class="section-label">Reference</div> 384 <h2>Query parameters</h2> 385 <table> 386 <tr><th>Parameter</th><th>Required</th><th>Description</th></tr> 387 <tr><td><code>lead</code></td><td>Yes</td><td>Lead object as JSON string</td></tr> 388 <tr><td><code>icp</code></td><td>Yes</td><td>Ideal Customer Profile description (plain text)</td></tr> 389 <tr><td><code>model</code></td><td>No</td><td>LLM model (default: <code>openrouter/auto</code>)</td></tr> 390 <tr><td><code>token</code></td><td>Yes</td><td>Your Apify API token</td></tr> 391 </table> 392 <h2 style="margin-top:24px">Headers</h2> 393 <table> 394 <tr><th>Header</th><th>Required</th><th>Description</th></tr> 395 <tr><td><code>X-OpenRouter-Key</code></td><td>No</td><td>Your OpenRouter API key for BYOK (keeps secrets out of URL logs)</td></tr> 396 </table> 397 </section> 398 399 <section class="section"> 400 <div class="section-label">Response</div> 401 <h2>Response format</h2> 402 <pre>{ 403 "id": 1, 404 "input": {"company": "Acme Corp", "title": "VP of Engineering"}, 405 "label": "VP of Engineering at Acme Corp", 406 "score": 85, 407 "band": "excellent", 408 "summary": "Strong fit: VP-level decision maker at mid-size SaaS company.", 409 "confidence": 0.9 410}</pre> 411 </section> 412 413 <section class="section"> 414 <div class="section-label">Scoring</div> 415 <h2>Score bands</h2> 416 <table> 417 <tr><th>Band</th><th>Score Range</th><th>Meaning</th></tr> 418 <tr><td><span class="badge">Excellent</span></td><td>80-100</td><td>Strong ICP match — prioritize for outreach</td></tr> 419 <tr><td><span class="badge">Good</span></td><td>60-79</td><td>Solid fit with minor gaps</td></tr> 420 <tr><td><span class="badge">Fair</span></td><td>40-59</td><td>Partial fit — worth reviewing</td></tr> 421 <tr><td><span class="badge">Poor</span></td><td>0-39</td><td>Does not match ICP</td></tr> 422 </table> 423 </section> 424 425 <section class="section"> 426 <div class="section-label">Cost</div> 427 <h2>Pricing</h2> 428 <p>Pay-per-event pricing on the Apify platform:</p> 429 <table> 430 <tr><th>Tier</th><th>Leads</th><th>Per 1,000</th></tr> 431 <tr><td>Base</td><td>Any</td><td>$1.00</td></tr> 432 <tr><td><span class="badge">Bronze</span></td><td>100+</td><td>$0.90</td></tr> 433 <tr><td><span class="badge">Silver</span></td><td>1,000+</td><td>$0.80</td></tr> 434 <tr><td><span class="badge">Gold</span></td><td>10,000+</td><td>$0.70</td></tr> 435 </table> 436 </section> 437 438 <section class="section"> 439 <div class="section-label">Auth</div> 440 <h2>Authentication</h2> 441 <p>Authenticate using either method:</p> 442 <ul> 443 <li>Query parameter: <code>?token=YOUR_APIFY_TOKEN</code></li> 444 <li>Header: <code>Authorization: Bearer YOUR_APIFY_TOKEN</code></li> 445 </ul> 446 <p style="margin-top:8px">Get your token from <a href="https://console.apify.com/settings/integrations">Apify Console → Settings → Integrations</a>.</p> 447 </section> 448 449 <section class="section"> 450 <div class="section-label">Superlative</div> 451 <h2>More from Superlative</h2> 452 <div class="product-grid"> 453 <a href="https://apify.com/superlativetech/superclean-company-names?fpr=8e9l1" class="product-card"> 454 <div class="product-name">Company Names <span class="status">Live</span></div> 455 <p class="product-desc">Clean company names for cold email and CRM.</p> 456 </a> 457 <a href="https://apify.com/superlativetech/superclean-job-titles?fpr=8e9l1" class="product-card"> 458 <div class="product-name">Job Titles <span class="status">Live</span></div> 459 <p class="product-desc">Standardize job titles for outreach sequences.</p> 460 </a> 461 <a href="https://apify.com/superlativetech/superclean-person-names?fpr=8e9l1" class="product-card"> 462 <div class="product-name">Person Names <span class="status">Live</span></div> 463 <p class="product-desc">Clean and format person names for personalization.</p> 464 </a> 465 <a href="https://apify.com/superlativetech/superclean-product-names?fpr=8e9l1" class="product-card"> 466 <div class="product-name">Product Names <span class="status">Live</span></div> 467 <p class="product-desc">Normalize product and brand names from exports.</p> 468 </a> 469 <a href="https://apify.com/superlativetech/supernet-domain-health?fpr=8e9l1" class="product-card"> 470 <div class="product-name">Domain Health <span class="status">Live</span></div> 471 <p class="product-desc">Check email deliverability and domain reputation.</p> 472 </a> 473 <a href="https://apify.com/superlativetech/dns-lookup?fpr=8e9l1" class="product-card"> 474 <div class="product-name">DNS Lookup <span class="status">Live</span></div> 475 <p class="product-desc">Look up DNS records for any domain.</p> 476 </a> 477 </div> 478 </section> 479 480 <footer> 481 <div class="footer-content"> 482 <p class="footer-text">© 2026 Superlative</p> 483 <div class="footer-links"> 484 <a href="https://apify.com/superlativetech?fpr=8e9l1">Apify Store</a> 485 </div> 486 </div> 487 </footer> 488</div> 489 490</body> 491</html>`; 492}

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", "_source": "eng" }, { "name": "Marc Goldman", "title": "Director - Industry Solutions", "company": "Esri", "location": "St Louis, Missouri, United States", "yearsAtCompany": 6.3, "summary": "With nearly three decades of experience in the Architecture, Engineering, Construction, and Infrastructure sector, I am a seasoned leader and strategist who delivers innovative and impactful technolog", "_source": "eng" }, { "name": "Doug Goldie", "title": "Founder", "company": "Code Cauldron", "location": "Denver, Colorado, United States", "yearsAtCompany": 15.9, "summary": "Seasoned Technologist with over 20 years experience building web applications.\n\n* Significant early-stage experience.\n* Very familiar with scaling challenges.\n* Focus on Productivity: technologies and", "_source": "eng" }, { "name": "Arun Mahajan", "title": "Senior Director, Software Engineering. CTO's office at Juniper Networks", "company": "Juniper Networks", "location": "Palo Alto, California, United States", "yearsAtCompany": 5.5, "summary": "Experienced senior director / software developer / technical manager for building AI/ML enhanced SaaS products, cloud native architectures, hyper-converged systems, network virtualization, cloud servi", "_source": "eng" }, { "name": "Vijay Narayanan", "title": "Director of Software Engineering", "company": "U.S. Bank", "location": "San Francisco Bay Area", "yearsAtCompany": 7.5, "summary": "When I’m not leading high-impact engineering teams that blend AI innovation with rock-solid financial services, I’m explaining to my kids why Monopoly money won’t deposit through our award-winning U.S", "_source": "eng" }, { "name": "Durga Prasad K", "title": "Salesforce Senior DevOps Release Manager/Architect", "company": "International Motors Ltd", "location": "Greater Chicago Area", "summary": "Over 11+ Years of Excellent experience on Salesforce DevOps, Salesforce Developer, Copado, AutoRabit, Jenkins, Gearset, BitBucket, GitHub, WorkBench, Dataloader, GitBash, Mulesoft, SAAS Tool Kit, Jir", "_source": "eng" }, { "name": "Rajesh CV (Cherukupalli)", "title": "CEO & Founder", "company": "Samvidh Technologies", "location": "Flower Mound, Texas, United States", "yearsAtCompany": 3.4, "summary": "As the CEO of Samvidh Technologies, I am passionate about helping customers maximize their investment in the Salesforce ecosystem through creative solutions to solve their business needs. I have over ", "_source": "eng" }, { "name": "Israel Ogundare", "title": "Senior Linux Engineer", "company": "MIT Lincoln Laboratory", "location": "Boston, Massachusetts, United States", "summary": "Linux & DevOps Engineer with 7+ years of experience in cloud computing, automation, and infrastructure management. Strong expertise in Kubernetes, Linux administration, CI/CD pipelines, security autom", "_source": "eng" }, { "name": "Sri AWS Cloud Micro Services API Development,Architect", "title": "Sr.Cloud Development Engineer, Cloud Solution Architect", "company": "AA SOFTWARE & NETWORKING PRIVATE LIMITED", "location": "Dallas-Fort Worth Metroplex", "yearsAtCompany": 6.5, "summary": "Note: \nWork Authorization: H1B | C2C or C2H only\nRole: Tech Lead, Solution Architect \nOpen to working across the US locations.\nLocation: Aubrey, TX, Near Dallas, TX\n\nSUMMARY\n\n•\t~25 Years of IT Experie", "_source": "eng" }, { "name": "Tony Zirnoon, CISSP", "title": "CBO / VP of Sales", "company": "AIRRIVED", "location": "United States", "summary": "Tony Zirnoon, CISSP - Actian | LinkedIn\nWith over 25 years in the IT and cybersecurity sector, Tony is a seasoned leader currently heading the Strategic Partnerships and Alliances for Americas at Acti", "_source": "eng" }, { "name": "Gennady Brin", "title": "Sr. Principal", "company": "Intelagen", "location": "Los Gatos, California, United States", "summary": "With over 20+ years of experience in the technology sector, I am a seasoned and versatile leader who helps enterprise customers and partners harness the power and potential of data and AI/ML in the cl", "_source": "eng" }, { "name": "Randy Stimpson", "location": "Greater Seattle Area", "summary": "Creative, life-long learner and well-rounded full-stack software architect/developer with a wide range of experience. I have participated all aspects of the software development process from formulati", "_source": "eng" }, { "name": "Adam Pippert", "title": "Principal Solutions Architect", "company": "Red Hat", "location": "Beaverton, Oregon, United States", "yearsAtCompany": 7.3, "summary": "Professionally, I have sold well into 9 figures worth of deals over the years, and have touched everything from the world's smallest x86 chips to the world's largest telecom networks. I straddle the ", "_source": "eng" }, { "name": "Jim Enright", "title": "President,Financial/Economic Analyst & Systems Architect/Systems Developer, Independent Consultant", "company": "Critical Decision Systems", "location": "Jacksonville, Florida, United States", "yearsAtCompany": 30.2, "summary": "jimenright@yahoo.com\njimenright@critisys.com\n\nSpecialties: data acquisition and analysis, financial/economic analysis of business operations, software/reporting systems, business process re-engineerin", "_source": "eng" }, { "name": "Alan W.", "title": "Director of Cybersecurity and Infrastructure", "company": "Hays Medical Center", "location": "Hays, Kansas, United States", "yearsAtCompany": 4.5, "summary": "I am a multi-talented, growth-focused, and strategic cyber security and IT infrastructure director well-known for maintaining high organizational and technical standards while coordinating projects an", "_source": "eng" }, { "name": "Naga Ala", "title": "Principal Architect (AI and Security)", "company": "Mastercard", "location": "New York, New York, United States", "summary": "I’ve always been fascinated by how technology can transform lives. My journey through the world of digital architecture has been driven by a desire to tackle complex challenges head-on and turn them i", "_source": "eng" }, { "name": "Marcelo Lorenzetti", "title": "Founder & Executive AI Strategist", "company": "SavvyLex", "location": "Brooklyn, New York, United States", "summary": "As lead architect for Lazard’s enterprise AI and application modernization strategy, I designed and delivered cloud-native platforms that support global financial services operations. I created a prop", "_source": "eng" }, { "name": "Dr. Abraham Regan PHD, MBA, PMP, CSP,", "title": "President", "company": "American IT Systems", "location": "United States", "yearsAtCompany": 5.8, "summary": "Abraham Regan is a distinguished leader with 20 years of unmatched expertise in IT staffing across the United States. A true visionary, Abraham holds a double MBA specializing in Human Resources, Info", "_source": "eng" }, { "name": "Jim Walnum", "title": "Software Engineer - Infrastructure", "company": "Unify", "location": "San Francisco Bay Area", "summary": "Senior infrastructure practitioner, developer and business analyst with demonstrated successes leading large global technology projects and implementing effective cloud-based solutions. Proven stakeho", "_source": "eng" }, { "name": "Sean Smith", "title": "Information Technology Operations Manager", "company": "VivoSense, Inc.", "location": "Los Angeles Metropolitan Area", "yearsAtCompany": 3.6, "summary": "Throughout my career, I have proven to be an innovative, adaptable, and strategic Information Technology Leader with over 15 years of experience delivering secure, scalable, and cost-effective cloud a", "_source": "eng" }, { "name": "Tom Fenton", "title": "Analyst and Head of EUC practice ", "company": "StorageReview.com", "location": "Ridgefield, Washington, United States", "yearsAtCompany": 7.8, "summary": "Key Contributor, Proven Sales Professional and Effective Educator. \n\nMore than 10 years of experience working with virtualization and cloud technologies and over 20 years of Enterprise IT involvement ", "_source": "eng" }, { "name": "Naga Eskala", "title": "Director of Data Science & AI", "company": "Carelon", "location": "Atlanta Metropolitan Area", "yearsAtCompany": 8.8, "_source": "eng" }, { "name": "Donnovan Wint, MBA, CCSP", "title": "Intentional Living | Farming Enthusiast | Past Technology Wangler | Investor | AI/ML Explorer", "company": "Living Intentionally", "location": "Florahome, Florida, United States", "yearsAtCompany": 1.7, "summary": "Embracing Intentional Living | Gardener and Farming Enthusiast | Past Technology Wangler | Investor and Entrepreneur | AI/ML Explorer | New Adventures Await!\"\n\n\nThrough the years I have excelled in in", "_source": "eng" }, { "name": "Madhu Joshi", "title": "President & CEO", "company": "RestonLogic LLC", "location": "Washington DC-Baltimore Area", "yearsAtCompany": 10.3, "summary": "Visionary technology leader with 25+ years of experience driving cloud transformation and cybersecurity strategies for enterprise organizations. Throughout my career, I've consistently delivered measu", "_source": "eng" }, { "name": "Paul A. Taylor", "title": "Head of Commercial Development. Superalloy, Investment Casting, and Forging. 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Persuasive, influential, and articulate, with excellent communication", "_source": "sales" }, { "name": "Alexander Betit", "title": "Account Executive", "company": "OpenFortune 🥠", "location": "New York City Metropolitan Area", "summary": "Experienced Sales Leader with a demonstrated history of rapid sales growth and scalable business development processes. Highly-skilled in prospecting, Sales Management, Software as a Service (SaaS), S", "_source": "sales" }, { "name": "Dennis J Walker Jr", "title": "Employee Benefits Producer", "company": "USI Insurance Services", "location": "Saratoga Springs, Utah, United States", "summary": "I’ve seen nearly everything there is to see with health plans and life insurance since obtaining an insurance license in 2011. I joined USI in 2025 because they aligned with my values and give me the ", "_source": "sales" }, { "name": "Andy Caraballo", "title": "Regional Sales Manager", "company": "Netskope", "location": "Weehawken, New Jersey, United States", "yearsAtCompany": 1, "summary": "As Netskope's Regional Sales Manager, my focus is on driving the adoption of cutting-edge cybersecurity solutions within top-tier enterprises. Specializing in SASE and SD-WAN, I have a reputation for ", "_source": "sales" }, { "name": "Les Baron", "title": "Regional Account Manager", "company": "Silke Communications", "location": "Seattle, Washington, United States", "summary": "Passionate client advocate, with history of success across numerous industries and career revenue creation and responsibility of over $35,000,000\n \n* Experienced in advertising (Print/Trade Show), wir", "_source": "sales" }, { "name": "Brian McMorris", "title": "Partner and Representative", "company": "Reshape Automation", "location": "Scottsdale, Arizona, United States", "summary": "Leading a team of 15 manufacturing consultants and service engineers, helping clients understand and implement robotics and \"Industry 4.0\" manufacturing solutions. \n\nI am an entrepreneur and business ", "_source": "sales" }, { "name": "Richard Mundy", "title": "Southern California Sales Representative", "company": "PING", "location": "Carlsbad, California, United States", "yearsAtCompany": 38.2, "summary": "Thank you for finding me on LinkedIn. Please let me know how I best support your business networking efforts and PING Golf needs. -𝑹𝒊𝒄𝒉𝒂𝒓𝒅 𝑴𝒖𝒏𝒅𝒚\n\n➤Background:\n35+ years of extensive golf i", "_source": "sales" }, { "name": "Natalie Niemeyer", "title": "Executive Oncology Account Specialist (Breast)", "company": "AstraZeneca", "location": "Fort Collins, Colorado, United States", "yearsAtCompany": 2.9, "summary": "Multiple National Golden Circle Sales Winner with a proven track record of success with 18 years of experience selling across many therapeutic areas and consistently achieving top sales performance by", "_source": "sales" }, { "name": "James Holodnak", "title": "Account Executive", "company": "Brex", "location": "New York, New York, United States", "yearsAtCompany": 1.6, "summary": "I am a self-starter with a proven ability to collaborate effectively within teams, fostering an atmosphere of innovation and growth. My experience in the classroom has equipped me with a unique perspe", "_source": "sales" }, { "name": "Roberta Reed", "title": "Office Manager, Agent, Marketing and Sales", "company": "George A. Reed Agency, Inc", "location": "Wexford, Pennsylvania, United States", "yearsAtCompany": 28.2, "summary": "Experienced Office Manager with a demonstrated history of working in the insurance industry. Skilled in Marketing Management, Sales, Management, Networking, and Community Service. Strong administrativ", "_source": "sales" }, { "name": "Michael Massa", "title": "Consultant", "company": "Pool Industry Sales & Marketing Consultant", "location": "Knoxville, Tennessee, United States", "yearsAtCompany": 1.1, "summary": "Retired Chief Commercial Officer - Explore Industries and Vice President of Sales - Hayward Holdings. Responsible for strategy, execution, and performance of sales and marketing activities across Nort", "_source": "sales" }, { "name": "Ray Hotz", "title": "Specialty Sales Representative GI", "company": "Nestlé Health Science", "location": "Tucson, Arizona, United States", "yearsAtCompany": 5.8, "summary": " Offering an extensive background based on formal training and decades of award-winning experience to include the past 20 years in the Pharmaceutical Sales profession demonstrating superior persona", "_source": "sales" }, { "name": "Maria Trysla", "title": "Revenue Growth Architect / GTM Executive Advisor", "company": "Octain ", "location": "Boulder, Colorado, United States", "yearsAtCompany": 2.7, "summary": "🔑 WHAT I DO:\nI specialize in designing and implementing data-driven, AI-enabled digital strategies that fuel exponential growth for SaaS, technology and media companies. With 25+ years of leadership,", "_source": "sales" }, { "name": "Susan Janiak", "title": "Chief Executive Officer", "company": "Holistic Nutrition Empowerment by Elizabeth Hogue", "location": "Greater Orlando", "summary": "Retired…no longer! Started business w/my daughter, ‘Holistic Nutrition Empowerment by Elizabeth Hogue’. Please check our website \nHNE-everystage.com\n\nAssisted w/ the film for Kingstone Media “No Vaca", "_source": "sales" }, { "name": "Cindy Campbell", "title": "Sales Representative", "company": "Big Orange Productions", "location": "Greater Boston", "yearsAtCompany": 19.5, "summary": "At Rx Return Services, my mission was to optimize pharmaceutical return and disposal, ensuring maximum client reimbursement and certified destruction of non-returnable products. My competencies in mar", "_source": "sales" }, { "name": "Vic B.", "title": "Sales Manager - Mid Market Business Sales ", "company": "Kazka AI Consulting", "location": "Los Angeles, California, United States", "yearsAtCompany": 1.6, "summary": "Victor Brew is a skilled sales professional with extensive experience in SaaS, enterprise solutions, and the Media & Entertainment industry. He excels at identifying customer needs, qualifying opportu", "_source": "sales" }, { "name": "Brea Browne", "title": "AI Infra Advisor - Account Executive", "company": "Nebius", "location": "Newport Beach, California, United States", "yearsAtCompany": 1, "summary": "***Hiring managers and recruiters - although your consideration is appreciated, I am currently not interested in pursuing a new role at this time.\n\nAs a highly motivated and results-driven professiona", "_source": "sales" }, { "name": "Dennis O'Neill, CTP", "location": "Greater Philadelphia", "summary": "Director of Credit and Collections who directly supports the Treasurer for all Credit/Collections needs. \nOffering a Diversified Business Background in Cash Management, Cash Forecasting, Working Capit", "_source": "sales" }, { "name": "William Patrick Burke", "title": "Specialty Sales Representative", "company": "LENZ Therapeutics", "location": "Sarasota, Florida, United States", "summary": "35 years of experience in the medical device industry; Spine Surgery, Neurosurgery, Critical Care, Orthopedics, Radiology & Ophthalmology. My core competencies include new business development, distri", "_source": "sales" }, { "name": "Andrew Markopoulos", "title": "Business Owner", "company": "Markopoulos Enterprises", "location": "Bel Air, Maryland, United States", "yearsAtCompany": 33.6, "summary": "Experienced and goal oriented professional with a proven track record as CEO and in the Sales and Marketing fields who has built and maintained customer centric relationships, while consistently hitti", "_source": "sales" }, { "name": "Rob Harrington, MBA", "title": "Sr. Account Executive ", "company": "Intuit Mailchimp", "location": "Atlanta, Georgia, United States", "summary": "Results-oriented senior sales professional with 20+ years of experience in the contact center and CX space, including solution sales for artificial intelligence, virtual assistant, agent performance i", "_source": "sales" }, { "name": "Stephen Fullerton", "title": "Senior Account Exec-Public Sector Sales", "company": "Pano AI", "location": "Grand Junction, Colorado, United States", "summary": "PROFESSIONAL PROFILE: A diverse professional career that includes: Sales, Marketing, Business Development, Field Engineering, and Technical Support Services. An experienced sales and marketing profess", "_source": "sales" }, { "name": "Robert Trainor", "title": "President", "company": "Trainor Group", "location": "Jupiter, Florida, United States", "yearsAtCompany": 22.4, "summary": "Experience Highlights: Direct sales of medical devices to hospitals, medical practices and medspas. Business development; communication skills; customer relations; marketing & marketing management; ", "_source": "sales" }, { "name": "Clarence Bunch Jr", "title": "Senior Director, Technology", "company": "Epsilon", "location": "Clinton Township, Michigan, United States", "yearsAtCompany": 2.7, "_source": "full" }, { "name": "Marc Goldman", "title": "Director - Industry Solutions", "company": "Esri", "location": "St Louis, Missouri, United States", "yearsAtCompany": 6.3, "summary": "With nearly three decades of experience in the Architecture, Engineering, Construction, and Infrastructure sector, I am a seasoned leader and strategist who delivers innovative and impactful technolog", "_source": "full" }, { "name": "Jacob Buckles", "title": "Senior Director of Digital Marketing", "company": "Frontier Internet", "location": "Dallas, Texas, United States", "yearsAtCompany": 1.4, "summary": "Passionate about utilizing technology and digital platforms to drive business growth and engaging customer experiences. Over 13 years of experience in the digital marketing industry in variety of cust", "_source": "full" }, { "name": "Mark Compton", "title": "HSE Manager", "company": "US. STEEL WORKS INC.", "location": "Greater Houston", "summary": "Career surrounds worldwide industrial construction / operational plant / offshore HSE management. \n\nPrimary Management Areas: Development - Execution - Monitoring of ITB, Contract Control, QHSE Proced", "_source": "full" }, { "name": "George M. Thomas product project manager SSBB,PMP.", "title": "Aviation ", "company": "Aviation & Aerospace Operations - Product Management , SSBB.", "location": "Greater Orlando", "yearsAtCompany": 18.2, "summary": "I’m seeking a Deputy Director, Deputy Administrator, Operations Manager, Emergency Manager, Chief of Staff or Branch Chief role, and am the perfect fit for these roles because I have the following rel", "_source": "full" }, { "name": "Virginia Albornoz", "title": "O&G Business Development Director | Consultant", "company": "Ayko Group", "location": "Houston, Texas, United States", "yearsAtCompany": 1.3, "summary": "I am a results oriented and self-driven Petroleum Engineer with extensive experience working in Latin America and USA on both onshore and offshore projects. Experienced in managing both people and pro", "_source": "full" }, { "name": "Brett Pasternak", "title": "Targeting IT Director | IT Senior Manager | IT Manager ", "company": "Seeking New Opportunities", "location": "Greater Tampa Bay Area", "summary": "I am a strategic, analytical, and results‑driven leader with more than a decade of experience in engineering, system design, and solution management. I excel at translating complex data into actionabl", "_source": "full" }, { "name": "Sundeep Kondaveeti 💡✨️", "title": "Data Science Manager", "company": "Michaels Stores", "location": "Austin, Texas Metropolitan Area", "summary": "Seasoned Data Science professional with 15 years of experience in automating key business insights and providing thought leadership in healthcare, retail, and hospitality domains. Tackled complex data", "_source": "full" }, { "name": "Tarek Hussien, CSSBB", "location": "Bethlehem, Pennsylvania, United States", "summary": "Tarek Hussien – Professional Bio\n\nTarek Hussien earned his B.S. degree in Mechanical Engineering from Helwan University in Cairo, graduating with high honors and making the Dean’s List. He went on to ", "_source": "full" }, { "name": "Ebot Eyong,PhD. CQE ,RAC(Device/Drug)", "title": "Sr. Quality and Regulatory Affairs Consultant/Manager/Director", "company": "E & E Medicals and consulting", "location": "Atlanta Metropolitan Area", "yearsAtCompany": 7.8, "summary": "Distinguished senior engineering consultant in regulatory affairs and quality assurance for advanced medtech, biotech, and pharmaceutical product development. A result-oriented biomedical, quality ass", "_source": "full" }, { "name": "Randall Hartley - Biotech/Pharma/Life Sciences Consultant", "title": "Senior Consultant / Director at Critical Mass Consulting, LLC", "company": "Critical Mass Consulting, LLC", "location": "San Francisco Bay Area", "yearsAtCompany": 6.3, "summary": "\nInnovative operations leader with entrepreneurial nature, proven change management skills, and a solid track record of success ensuring quality and supercharging healthcare, pharma, and biotech busin", "_source": "full" }, { "name": "Scott Kesner", "title": "Director of Recruiting", "company": "Full Spectrum", "location": "Greater Boston", "yearsAtCompany": 4.2, "summary": "Highly resourceful, creative and dexterous in facilitating the full life cycle process of recruitment, involving practical application of direct recruiting, data mining, networking, relationship build", "_source": "full" }, { "name": "Brett Rogers", "title": "Sr. Director Product Management", "company": "Charter Communications", "location": "Denver Metropolitan Area", "yearsAtCompany": 5.6, "summary": "Product Manager, Technologist, Strategic Partnerships (Business Development), and Team Cheerleader.\n\nI love to find and solve problems for customers and partners. I spend a lot of time with partners w", "_source": "full" }, { "name": "Jorge Alvarez", "title": "Lead Consultant", "company": "Dynamic Process and Project Services", "location": "West Palm Beach, Florida, United States", "yearsAtCompany": 1.4, "summary": "Solar and operations executive with a background in solar construction and maintenance, global supply chain (procurement, logistics, distribution), consultancy and program/project management for opera", "_source": "full" }, { "name": "Nasos Bardis", "title": "General Manager / Consultant", "company": "Private Company", "location": "Dallas, Texas, United States", "yearsAtCompany": 1.3, "summary": "At the forefront of Engineering endeavors, my role engages operational excellence, alignment of company’s business objectives with stringent regulatory compliance and project management execution, lea", "_source": "full" }, { "name": "William Oliveira - Chemical Engineer/Sixϭ BB.", "title": "International Consultant - Business Development, Operational Excellence & Industrial Efficiency", "company": "Kairos Innova Gestão & Inovação", "location": "St Augustine, Florida, United States", "yearsAtCompany": 1.4, "summary": "Senior operations and manufacturing leader with 20+ years of experience in chemical and specialty manufacturing, leading plant operations and large teams across the U.S. and Latin America, with full a", "_source": "full" }, { "name": "Juan Merelo", "title": "Founder & Principal Consultant", "company": "Corporate Cyber Control", "location": "Atlanta, Georgia, United States", "summary": "With over two decades in IT leadership, I specialize in building and securing robust IT infrastructures that drive business growth. As the IT services manager and CISO at Pratt Industries for 25 years", "_source": "full" }, { "name": "Ralph Wallace", "title": "Independent Consultant", "company": "Self-employed", "location": "Bastrop, Texas, United States", "yearsAtCompany": 1.5, "summary": "Experience: Over 45 years technology experience in executive management, program and project management, engineering management, and capture management roles of ever increasing responsibility. Recogni", "_source": "full" }, { "name": "Leland Sparks", "title": "Chief Datacenter Engineer", "company": "Egil Wings, LLC", "location": "Sandy, Oregon, United States", "yearsAtCompany": 1.2, "summary": "I am a Global Data Center Consultant who drives the direction of the data center from the design stage, to position the company as an innovator on the forefront of technology, while minimizing power c", "_source": "full" }, { "name": "Paul Albert", "title": "Marine Consultant", "company": "Albert Marine Consultants", "location": "Grand Bay, Alabama, United States", "yearsAtCompany": 8.4, "summary": "Since my retirement in 2017 assisted both shipyards and vessel Owners in the following areas:\n\nResearch and Development. Proposal Writing and Red Team Reviews, project estimate reviews, Shipyard faci", "_source": "full" }, { "name": "Michael Kirschner", "title": "President/Manager", "company": "Design Chain Associates, LLC", "location": "San Francisco, California, United States", "yearsAtCompany": 10.8, "summary": "I help manufacturers understand and ensure that their products comply with health and environmental regulatory, customer and market requirements.\n\nI have broad expertise in areas including semiconduct", "_source": "full" }, { "name": "Ashok Adur, Ph.D.", "title": "President & Consultant", "company": "Everest International Consulting (LLC)", "location": "Jacksonville, Florida, United States", "yearsAtCompany": 33.7, "summary": "Outstanding record of providing innovative & disruptive solutions and improving top & bottom-line results by developing high margin value-added products, improving productivity & reducing costs. Custo", "_source": "full" }, { "name": "Robert Gonzalez", "title": "Executive Advisor", "company": "LevelUp Success Innovations", "location": "Tracy, California, United States", "yearsAtCompany": 1.9, "summary": "I'm driven by a relentless curiosity and a daily desire to make meaningful impact. I believe technology should simplify our lives—seamlessly integrated, almost invisible. When used right, it doesn't f", "_source": "full" }, { "name": "Jeff Rowe", "location": "Framingham, Massachusetts, United States", "summary": "SUMMARY---\nA results-oriented professional with a proven track record in Retail, Cannabis, Construction, and People Leadership. \n\nAreas of Knowledge & Expertise:\nSales, Operations, HR/People/Diversity", "_source": "full" }, { "name": "Janardhan Saithala, PhD, MBA", "title": "Senior Consultant", "company": "Blade Energy Partners", "location": "Cypress, Texas, United States", "yearsAtCompany": 1.5, "summary": "I’m an asset integrity and operational excellence leader with 18+ years across upstream and midstream oil and gas, CCUS, hydrogen, and industrial operations. My career has been built on improving reli", "_source": "full" }, { "name": "Stephanie Pearcy", "title": "CEO", "company": "Pearcy Household, LLC", "location": "San Diego, California, United States", "summary": "I'm a mother of 4 children; 2 girls ages 11 and 9, and 2 boys, ages 6 and 4. I've worked for 20 years in many different capacities from counselor in a boys' home to estimating closing costs for houses", "_source": "misc" }, { "name": "Pamela T.", "title": "CAO", "company": "Tapp Homestead", "location": "Greater Hattiesburg Area", "yearsAtCompany": 14.4, "summary": "Versatile skill set developed through experience as a Vice President, Grand Jury Administrator, Executive Assistant, and Assistant Manager. Recognized throughout career for being a trusted executive ", "_source": "misc" }, { "name": "Laura Lalley", "title": "Medical Adjuster", "company": "Midwest Insurance Company", "location": "Clarksville, Tennessee, United States", "yearsAtCompany": 6.1, "_source": "misc" } ]

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Italian Restaurant, Lunch & Corporate Catering", "industry": "Coffee shop", "location": "New York, New York", "description": "Self-serve take-out spot offering gourmet Mediterranean sandwiches, salads & pastas.", "website": "https://mangia.nyc/", "rating": 4.7, "reviewCount": 317 }, { "company": "KYU NYC", "industry": "Asian restaurant", "location": "New York, New York", "description": null, "website": "https://www.kyurestaurants.com/location/kyu-nyc/?utm_source=gmb", "rating": 4.4, "reviewCount": 697 }, { "company": "Local 92", "industry": "Mediterranean restaurant", "location": "New York, New York", "description": "Informal Middle Eastern restaurant also serving American eats in cozy, rustic digs with a piano.", "website": "https://local92ny.com/", "rating": 4.2, "reviewCount": 1020 }, { "company": "Tucci New York City", "industry": "Italian restaurant", "location": "New York, New York", "description": null, "website": "https://www.tuccinyc.com/", "rating": 4.3, "reviewCount": 292 }, { "company": "Jack's Wife Freda", "industry": "Mediterranean restaurant", "location": "New York, New York", "description": "Lively bistro executing American-Mediterranean cooking & classic cocktails in understated digs.", "website": "https://jackswifefreda.com/", "rating": 4.4, "reviewCount": 4264 }, { "company": "The Grey Dog", "industry": "American restaurant", "location": "New York, New York", "description": "Neighborhood coffeehouse serving eggs, granola, sandwiches & salads in a homey, laid-back setting.", "website": "http://www.thegreydog.com/", "rating": 4.4, "reviewCount": 1942 }, { "company": "C as in Charlie", "industry": "Korean restaurant", "location": "New York, New York", "description": null, "website": "http://c-asincharlie.com/", "rating": 4.8, "reviewCount": 836 }, { "company": "LOS TACOS No.1", "industry": "Taco restaurant", "location": "New York, New York", "description": "Bustling taqueria serving tacos, quesadillas & aguas frescas in a street-style setup (no seating).", "website": "http://www.lostacos1.com/", "rating": 4.8, "reviewCount": 1569 }, { "company": "Araf Biriyani & Halal Food", "industry": "Halal restaurant", "location": "New York, New York", "description": null, "website": null, "rating": 4.7, "reviewCount": 182 }, { "company": "Forsythia NYC", "industry": "Italian restaurant", "location": "New York, New York", "description": "Housemade pasta & creative mains turned out in a charming eatery that has outdoor seating.", "website": "http://forsythianyc.com/", "rating": 4.4, "reviewCount": 409 }, { "company": "Fanelli Café", "industry": "Traditional American restaurant", "location": "New York, New York", "description": "Simple pub grub, beer & cocktails are served in this classic old SoHo pub, dating back to 1847.", "website": "https://fanellicafe.nyc/", "rating": 4.3, "reviewCount": 1591 } ]