# Funding Round Tracker (Stage + Amount + Investor + Recency) (`fetchcraft/funding-round-tracker`) Actor Drop in company URLs. Get back latest funding round (stage, amount, date, lead investor, evidence quote) plus funding history, recency, runway estimate. Just-funded companies are the top B2B target with a 60 to 90 day procurement window. Pay per result. No subscription. - **URL**: https://apify.com/fetchcraft/funding-round-tracker.md - **Developed by:** [Emily Ward](https://apify.com/fetchcraft) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Funding Round Tracker > Drop in a list of company URLs. Get back: latest funding round (stage, amount, lead investor, year), full funding history, recency rating, and an AI-generated buying window assessment. > > Just-funded companies have a 60 to 90 day aggressive procurement window. This actor tells you who is in it right now. ### What this solves Timing is the biggest variable in B2B sales. The same pitch that fails at Month 13 (after the procurement window has closed) closes instantly at Month 2 (when they just raised and are buying aggressively). This actor tells you where each prospect sits in that cycle. ### What you get per URL ```json { "input_url": "https://linear.app", "company_name": "Linear", "mode": "ai", "has_funding_signal": true, "latest_stage": "series-c", "latest_amount_usd_m": 82, "latest_lead_investor": "Accel", "latest_year_hint": 2024, "latest_evidence_quote": "Linear closed an $82M Series C led by Accel...", "latest_confidence": "high", "recency": "recent", "funding_history": [ { "stage": "series-c", "amount_usd_m": 82, "lead_investor": "Accel", "year_hint": 2024, "confidence": "high" }, { "stage": "series-b", "amount_usd_m": 35, "lead_investor": "Sequoia", "year_hint": 2022, "confidence": "high" } ], "total_raised_usd_m": 117, "stage_proxies": { "founded_year": 2019, "customer_count_signal": 25000 }, "ai_insights": { "estimated_stage": "series-c", "runway_assessment": "Strong, ~24-36 months on current burn", "buying_window": "active, 12 months from last round so aggressive procurement window is past but still spending", "sales_pitch_angle": "Pitch tools that scale with multi-region distributed engineering team", "key_investor_signals": "Accel + Sequoia signal sustained product-led growth trajectory" } } ```` ### The buying window model | Round recency | `recency` value | Buying behavior | |---|---|---| | Under 3 months | `very_recent` | Aggressive: buying fast and broadly | | 3 to 12 months | `recent` | Active: most procurement underway | | 12 to 24 months | `moderate` | Selective: tighter evaluation | | Over 24 months | `older` | Cautious: ROI focus, likely approaching next raise | | No signal | `none` | Bootstrapped or signal not found | ### Modes #### Preview (free) 1 URL only, no charge. Use to test the output before running a paid batch. #### Regex ($0.20 per result, recommended for bulk) - Fetches homepage plus 11 common press / about / investors / news paths - Sentence-level pattern matching for funding signals: stage + amount/investor/verb combinations - Extracts evidence quote (the exact sentence the signal was found in) - Computes recency from year hint - Extracts soft stage proxies: founded year, customer count signal, team size signal, revenue signals **Honest limitation:** Regex detects signals in static text only. Companies that haven't published a press release or don't mention funding publicly will return `has_funding_signal: false` even if they have raised. AI mode uses inference to fill some of these gaps. #### AI-enhanced ($0.40 per result) Runs regex, then Claude reads up to 5 pages (homepage, about, press, investors, news/blog) to: - Find non-obvious funding signals (investor logos, portfolio pages, "backed by" mentions) - Infer funding stage from proxies when direct signal is absent - Generate runway assessment and buying window classification - Identify the best sales pitch angle given the company's stage and growth trajectory #### AI deep ($0.60 per result) Same as AI-enhanced but also reads the latest 2 blog posts or press releases for the freshest signals. ### Input format ```json { "urls": ["https://linear.app", "https://notion.so"], "mode": "regex" } ``` - `urls`: array of company URLs (homepage preferred) - `mode`: `"preview"` | `"regex"` | `"ai"` | `"ai_deep"` (default: `"regex"`) ### Who uses this - **SDRs and AEs** who want to prioritise just-funded companies in their outreach queue - **VCs and angels** tracking portfolio company growth trajectories - **BD and partnerships** teams finding well-funded strategic partners - **Investors** doing preliminary diligence on private companies - **Competitive intelligence** teams monitoring funded competitors ### FAQ **Q: What if a company is bootstrapped and never raised?** The actor returns `has_funding_signal: false` and `recency: "none"`. The `stage_proxies` block still returns available signals (founded year, customer count). AI mode can infer approximate stage from these proxies. **Q: How do you know the year of the round?** From the evidence text. If the year is not explicit, the actor returns `year_hint: null` and `recency: "unknown"`. **Q: Can I filter results by recency?** Yes. Use Apify's dataset filtering in the UI, or pipe the dataset into your own code and filter on the `recency` field. **Q: What's the typical hit rate?** In regex mode: approximately 45% of companies have detectable funding signals on their site. AI mode raises this to approximately 70% (by reading investor pages and inferring from proxies). ### The B2B Sales Intelligence Suite This actor is part of a 4-actor suite by Emily Ward that turns a raw TAM list into a ranked, personalised outreach queue: 1. **[Hiring Signal Detector](https://apify.com/fetchcraft/hiring-signal-detector)**: who's expanding? 2. **[Funding Round Tracker](https://apify.com/fetchcraft/funding-round-tracker)** (you are here): who has fresh capital? 3. **[SaaS Spend Scanner](https://apify.com/fetchcraft/saas-spend-scanner)**: what do they pay for? 4. **[AI Sales Personalizer](https://apify.com/fetchcraft/ai-sales-personalizer)**: write the opener. Used together, they 3x outbound conversion vs working from a raw TAM list. What used to take a 5-person SDR team a week takes 1 person 2 hours and ~$95 AUD in Apify credits. *** Tags: `funding` `venture-capital` `crunchbase` `b2b` `sales-intelligence` `startup` `investment` `lead-enrichment` Made by Emily Ward, Founder of Cancel Costs. Questions: emily@cancelcosts.com # Actor input Schema ## `urls` (type: `array`): List of company URLs. The actor auto-discovers /about, /press, /news, /investors pages. ## `mode` (type: `string`): regex: pattern-match funding signals from press / about pages, ~A$0.20 per result. ai: regex + Claude structured extraction of full funding history with stage, amount, investors, runway estimate, ~A$0.60 per result. preview: 1 URL only, not charged. ## `only_funded` (type: `boolean`): If true, skip companies where no funding signal is detected. Still charged (you paid for the discovery work). Set false to see all results including 'no signal found'. ## `max_concurrency` (type: `integer`): How many URLs to process in parallel. ## Actor input object example ```json { "urls": [ "https://www.notion.so", "https://www.figma.com", "https://www.linear.app" ], "mode": "regex", "only_funded": false, "max_concurrency": 5 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "urls": [ "https://www.notion.so", "https://www.figma.com", "https://www.linear.app" ] }; // Run the Actor and wait for it to finish const run = await client.actor("fetchcraft/funding-round-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "urls": [ "https://www.notion.so", "https://www.figma.com", "https://www.linear.app", ] } # Run the Actor and wait for it to finish run = client.actor("fetchcraft/funding-round-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "urls": [ "https://www.notion.so", "https://www.figma.com", "https://www.linear.app" ] }' | apify call fetchcraft/funding-round-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fetchcraft/funding-round-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Funding Round Tracker (Stage + Amount + Investor + Recency)", "description": "Drop in company URLs. Get back latest funding round (stage, amount, date, lead investor, evidence quote) plus funding history, recency, runway estimate. Just-funded companies are the top B2B target with a 60 to 90 day procurement window. Pay per result. No subscription.", "version": "0.1", "x-build-id": "KIZfTwYCUgyiJNnYM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fetchcraft~funding-round-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fetchcraft-funding-round-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fetchcraft~funding-round-tracker/runs": { "post": { "operationId": "runs-sync-fetchcraft-funding-round-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fetchcraft~funding-round-tracker/run-sync": { "post": { "operationId": "run-sync-fetchcraft-funding-round-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "urls" ], "properties": { "urls": { "title": "Company URLs", "type": "array", "description": "List of company URLs. The actor auto-discovers /about, /press, /news, /investors pages.", "items": { "type": "string" } }, "mode": { "title": "Mode", "enum": [ "preview", "regex", "ai" ], "type": "string", "description": "regex: pattern-match funding signals from press / about pages, ~A$0.20 per result. ai: regex + Claude structured extraction of full funding history with stage, amount, investors, runway estimate, ~A$0.60 per result. preview: 1 URL only, not charged.", "default": "regex" }, "only_funded": { "title": "Only return companies with funding signal", "type": "boolean", "description": "If true, skip companies where no funding signal is detected. Still charged (you paid for the discovery work). Set false to see all results including 'no signal found'.", "default": false }, "max_concurrency": { "title": "Max parallel requests", "minimum": 1, "maximum": 15, "type": "integer", "description": "How many URLs to process in parallel.", "default": 5 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```