# Scout β€” Lead Enrichment + OSINT (`logical_vivacity/scout`) Actor Email finder + lead enrichment + OSINT from public sources. Pass any fragment β€” name, email, or domain β€” get a verified dossier: 700+ identity sites, SMTP-validated emails, document mining, sanctions screen, domainβ†’team discovery. $0.05 person, $0.15 domain. No API keys - **URL**: https://apify.com/logical\_vivacity/scout.md - **Developed by:** [Logical Vivacity](https://apify.com/logical_vivacity) (community) - **Categories:** Lead generation, AI, News - **Stats:** 5 total users, 4 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 1,000 person enricheds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Scout - OSINT + Lead Enrichment from Public Sources > **Send Scout out with any fragment - a name, an email, a domain, a handle - and it brings back a verified, audit-ready dossier: cross-platform identity, work emails, employer firmographics, document evidence, and the org's actual team. No customer API keys. No per-seat pricing. Pay only per result.** Scout is a single Apify actor that spans the gap between an OSINT tool and a lead-enrichment platform. From a single field of input it returns a structured JSON dossier: verified identity, social presence across 700+ platforms, work-email waterfall, public document evidence, sanctions screening, full company firmographics - and when you scout a domain, the org's actual people, each spawned as a related entity and enriched in the same run. **Pricing:** $0.05 per person, $0.15 per domain/org, $0.02 per spawned team member. Compute on top (Apify default). No subscriptions, no API keys, no surprises. --- ### What's in the box - πŸ” **Org β†’ People discovery.** Pass `domain: "acme.com"` and Scout walks the team / about / leadership pages, NER-extracts each person, pairs them with their title, and **spawns a Person entity per teammate** - then runs the full person-enrichment pipeline on each (email finder, GitHub, LinkedIn, Gravatar, …). One domain input β†’ fully populated team graph. - πŸ“§ **Email finder waterfall.** Given `(name, domain)` Scout generates plausible local-parts (`first.last`, `flast`, `firstl`, …), runs SMTP RCPT against each, returns the first verified hit with full provenance. - πŸ“„ **Document mining.** Filename signals (date / kind / subject), embedded PDF/DOCX metadata (Author / Producer / Created), OCR fallback for image-only PDFs, NER-based co-occurrence with proximity scoring (closer name = stronger relation), section-aware resume parsing β†’ structured `WorkExperience` and `EducationEntry` entries. - πŸ”— **High-signal individual systems.** Booking links (Calendly, cal.com, SavvyCal, Hubspot Meetings, …). Newsletter detection (Substack, Beehiiv, Buttondown, Kit, Ghost). Cert Transparency for subdomain history. - πŸ₯· **Stealth fetch.** httpx-first with smart browser fallback for anti-bot hosts, `playwright-stealth` patches, randomised viewport, Google Referer header, and a curated list of "go straight to browser" hosts (LinkedIn, Twitter, Glassdoor, Crunchbase, …). - 🧹 **Field normalization** at the model level. Phones canonicalise to E.164, dates to ISO, URLs lose `www.` / fragments / trailing slashes, handles drop leading `@`, emails lowercase, LinkedIn URLs canonicalise to `https:///in/`. - ⚑ **Single-entity quick mode.** No more "wrap in `entities: [...]`" - just paste `full_name` or `email` or `domain` directly into the input. - πŸ“œ **Per-component provenance.** Every component carries `_added_by`, `_added_at`, `_confidence`, `_sources`, `_evidence` - your compliance team can audit every datum. --- ### Two ways to brief Scout #### 1) Quick mode (typed inputs, single entity) Just fill the fields you have. No JSON wrapping required. ```json { "full_name": "Jane Doe", "email": "jane@acme.com" } ```` ```json { "domain": "acme.com" } ``` ```json { "linkedin_url": "https://www.linkedin.com/in/jane-doe" } ``` #### 2) Bulk mode (entities array) For multi-lead runs. ```json { "entities": [ { "kind": "person", "full_name": "Jane Doe", "email": "jane@acme.com" }, { "kind": "domain", "domain": "example.com" }, { "kind": "organization", "name": "Acme Inc", "domain": "acme.com" } ] } ``` Scout infers `kind` from whatever fields you pass - set it explicitly only when you want to override the heuristic. *** ### Input field reference All fields are optional individually; pass at least one. #### Person fields | Field | Type | Notes | |---|---|---| | `full_name` | string | Most useful single-anchor input | | `first_name` / `last_name` | string | Use if you only have parts | | `email` | string | Auto-validated (syntax, MX, SMTP, breach) | | `phone` | string | Any format β†’ E.164 | | `company_name` | string | Combined with `full_name` enables email finder | | `title` | string | Job title / role | | `location` | string | City / country - for disambiguation | | `linkedin_url` | string | Auto-canonicalised | | `github_username` | string | Stripped of `@`, lowercased | | `twitter_handle` | string | Stripped of `@`, lowercased | | `bluesky_handle` / `mastodon_handle` | string | | | `notes` | string | Free-form context attached to the entity | #### Organization / domain fields | Field | Type | Notes | |---|---|---| | `domain` | string | Triggers the full org pipeline + team discovery | | `name` / `company_name` | string | Org / company name | #### Run controls | Field | Type | Default | Notes | |---|---|---|---| | `kind` | enum | auto | `person` / `organization` / `domain` / `email` / `phone` / blank | | `processors` | array | all | Subset of enrichment systems (advanced) | | `proxyConfiguration` | proxy | Apify proxy on | Strongly recommend keeping enabled | | `headless` | boolean | true | Browser headless | | `perLeadTimeoutSeconds` | int | 180 | Total runtime ceiling per top-level entity | *** ### What Scout brings back per run #### Identity & verification - Verified `FullName`, `Email`, `Phone` (E.164), `Location`, primary social handles - Cross-source `Confirmed` components per field with which sources agreed - `Conflict` components surfacing values Scout *didn't* commit to - `SelfGrade` - per-field confidence + an overall `identity_locked` flag + rationale - `EntityTypeClassification` - developer / executive / academic / creator / marketer / unknown - `QualityGate` with input-ambiguity score and suggested extra inputs #### Email - RFC syntax + deliverability + MX + SMTP RCPT - Disposable + public-mailbox detection - Domain-level breach exposure (HaveIBeenPwned) - `EmailPattern` detection (`first.last@`, `flast@`, …) - **Email finder** - generates `name@domain` candidates and SMTP-verifies them when you have a name + an org domain anchor #### Social & public presence - Bluesky, Mastodon, Reddit, Stack Overflow, Dev.to, Medium, Hacker News, Wikipedia/Wikidata - Keybase + PGP keyservers - Cross-platform handle map: probes ~700 sites via WhatsMyName (GitHub, GitLab, npm, PyPI, Hugging Face, Kaggle, Behance, Twitch, YouTube, Substack, Steam, ProductHunt, Strava, Letterboxd, …) - Per-platform false-positive filtering against the lead's known name + location - `BookingLink` - Calendly / cal.com / SavvyCal / Tidycal / Hubspot Meetings / Acuity / Bookings / Doodle / YCBM - `Newsletter` - Substack / Beehiiv / Buttondown / Kit / Ghost / Revue #### Document evidence - Resume / CV / slide-deck discovery via dorked search - PDF / DOCX text extraction + emails / phones / URLs / hyperlinks - Embedded doc metadata: `doc_title`, `doc_author`, `doc_subject`, `doc_producer`, `doc_creator`, `doc_created`, `doc_modified` - **Filename parser** - extracts `parsed_date`, `kind_hint` (resume / cv / deck / report / invoice / contract / thesis / photo / …), `subject_hint` - **OCR fallback** - image-only PDFs retried via `tesseract` + `pdf2image` - **Section-aware resume parser** - emits structured `WorkExperience` (title, company, location, start/end dates, bullets) and `EducationEntry` (institution, degree, field, dates) - **NER co-occurrence** - extracts `PERSON` / `ORG` / `GPE` (location) entities from doc text with **proximity scoring** vs the primary person's name (closer = more related) - **MentionedWith** relation between people who appear together in the same document #### GitHub depth (developer leads) - Profile + organisation stats - Public repos, top languages, most-starred repo - Recent activity heatmap, timezone inference, most-active hour/day - Repo README mining for emails - Commit-author email extraction (skips `users.noreply.github.com`) - Co-author / collaborator graph - Package ownership across npm, PyPI, crates.io #### Compliance & risk - OFAC SDN sanctions screen (free public source) - PEP / adverse-news search - Domain-level breach history #### Company / domain side - WHOIS - registrar, dates, registrant org - DNS - A, MX, NS, TXT, SPF, DMARC - Hosting - ASN, ASN organisation, country - MX provider detection - Google Workspace / Microsoft 365 / Zoho / self-hosted - Tech-stack fingerprint via Wappalyzer - CDN detection (Cloudflare, Fastly, Akamai, Vercel, Netlify, …) - **Cert Transparency** subdomain history + cert-issuance emails (crt.sh) - Subdomain enumeration - Status pages, public API docs - ProductHunt history, Wayback Machine timeline - LinkedIn company page (auth-walled fields are skipped, not faked) - ATS / hiring signals - Greenhouse, Lever, Ashby, Workable - Crunchbase, Glassdoor, BuiltWith - **OrgPeople** - scrapes team / about / leadership pages, spawns a Person entity per teammate, enriches each *** ### Single-input demo flows #### Just a name ```json { "full_name": "Jane Doe" } ``` β†’ Scout anchors via dork search + identifier harvest β†’ finds GitHub, LinkedIn, Twitter, personal domain β†’ mines personal site for emails/handles β†’ cross-corroborates β†’ emits `Confirmed` on the agreed fields. #### Just a domain ```json { "domain": "acme.com" } ``` β†’ Full domain enrichment (WHOIS, DNS, hosting, tech stack, cert history) β†’ scrapes `/about` (browser + networkidle so SPA content renders) β†’ spawns a Person entity per teammate found on the team page β†’ runs email finder + GitHub + LinkedIn + Gravatar on each β†’ returns one org with N enriched related Persons. #### Email + company ```json { "email": "founder@acme.com", "company_name": "Acme Inc" } ``` β†’ Validates the email, mines breach data, checks SMTP β†’ mines pattern β†’ runs domain enrichment β†’ infers WorksFor β†’ completes person profile from socials. *** ### Pricing Pay only for results Scout actually delivers. No monthly fee, no per-seat licence, no API keys to manage. | Event | When it fires | Price | |---|---|---| | `person_enriched` | One Person / Email / Phone primary entity comes back enriched | **$0.05** | | `domain_enriched` | One Domain / Organization primary entity comes back enriched | **$0.15** | | `team_member_spawned` | A teammate found via orgβ†’people discovery and enriched as a related Person | **$0.02** each | A typical run: - `{full_name: "Jane Doe"}` β†’ **$0.05** (single person) - `{email: "founder@acme.com"}` β†’ **$0.05** (email expanded into person) - `{domain: "acme.com"}` (returns 8 teammates) β†’ **$0.15 + 8 Γ— $0.02 = $0.31** Scout does **not** bill when the result is too thin to be useful (`SelfGrade.overall_confidence < 0.2` and identity not locked) - you only pay for runs that actually delivered something. Apify charges its standard compute fee on top (typically a few cents per run depending on memory + duration). *** ### Use cases - **Sales / lead enrichment** - turn a sparse CRM record into a usable contact + employer dossier; or expand a single domain into a team prospect list with verified emails. - **OSINT / due diligence** - investigate a counterparty, verify identity across multiple independent sources, catch sanctions / adverse-news flags. - **Recruiting** - enrich a candidate's full public footprint, structured employment history from their resume, signals across 700+ sites. - **CRM hygiene** - re-enrich existing leads, surface stale or wrong-person records, dedupe via cross-source identity verification. - **Investigative reporting** - public-source person lookup with per-field provenance. - **Company research** - go from a domain to a fully enriched org + team, including booking links and newsletter URLs for outreach. *** ### Output shape Each input entity becomes one dataset record: ```json { "primary": { "kind": "person", "id": "...", "FullName": { "value": "Jane Doe", "_added_by": "input", "_added_at": "..." }, "Email": { "address": "jane@acme.com", "_confidence": 0.85, "_sources": ["email_finder"] }, "GitHubProfile": { "username": "janedoe", "followers": 142, "..." : "..." }, "LinkedInUrl": { "value": "https://www.linkedin.com/in/jane-doe" }, "WorkExperience": [ { "title": "Senior Software Engineer", "company": "Acme Inc", "start_date": "2022-01", "end_date": "Present", "bullets": [...] } ], "EducationEntry": [ { "institution": "Stanford University", "degree": "MSc", "field": "Computer Science", "start_date": "2018", "end_date": "2020" } ], "BookingLink": [{ "provider": "calendly", "url": "https://calendly.com/jane-doe" }], "DocEntityMention": [ { "entity_type": "person", "value": "John Smith", "proximity_score": 0.97, "min_distance_chars": 33 } ], "WorksFor": [{ "target_id": "...", "confidence": 0.85, "evidence": ["..."] }], "Confirmed": [{ "field": "email", "value": "jane@acme.com", "confidence": 0.95 }], "SelfGrade": { "overall_confidence": 0.78, "identity_locked": true, "evidence_strength": "strong" }, "LeadScore": { "score": 72, "tier": "hot", "persona": "developer" } /* + 30+ more component blocks, each stamped with provenance */ }, "related": [ { "kind": "organization", "id": "...", "FullName": { "value": "Acme Inc" }, "OwnsDomain": [...] }, { "kind": "domain", "id": "...", "Domain": { "value": "acme.com" }, "WhoisData": {...}, "HomepageData": {...} } ], "_meta": { "ticks_run": 4, "ran": {...}, "skipped": {...}, "failed": {...}, "elapsed_s": 137.4 } } ``` Every component carries `_added_by` (which system emitted it), `_added_at` (UTC timestamp), `_confidence`, `_sources`, and `_evidence` - so the output is fully audit-able. *** ### How does Scout compare? | | Scout | Apollo / ZoomInfo / Clearbit | Hunter.io | OSINT Industries | |---|---|---|---|---| | Data source | Public web only - every value tagged with origin | Proprietary database | Email guesses + verification | Public + private mix | | API key required | None | Yes (paid) | Yes (paid) | Yes (paid) | | Pricing | Per-result, cents per lead | $1K–$30K+ / yr per seat | $50–$500+ / mo | Subscription | | Identity verification | Cross-source confidence + surfaced conflicts | Opaque "verified" stamps | Email-only | Mixed | | Domain β†’ team people | βœ… Spawn each + enrich in same run | Yes (db) | No | No | | Email finder + SMTP verify | βœ… Built in | Yes (db) | βœ… Yes | No | | Resume / PDF mining | βœ… Built in (incl. OCR) | Limited | No | No | | GitHub depth | βœ… Commits, repos, co-authors, packages | None | No | Limited | | OFAC / sanctions | βœ… Built in | Add-on | No | Yes | | Output is auditable | βœ… Full ledger + per-component provenance | No | No | Mixed | | Self-hostable | βœ… Run on your own Apify account | No | No | No | Scout isn't a 200M-row contact DB. It's a *verifiable*, *one-shot* dossier per lead, paid by the result, with provenance your compliance team can audit. *** ### FAQ **How do I find someone's email from just their name?** Pass `full_name` and (optionally) `company_name` or `domain`. Scout probes public sources, mines documents and READMEs, runs cross-platform handle searches, and - when a corporate domain is involved - generates plausible work-email patterns and SMTP-verifies them. Success rate is highest when you provide at least one anchor beyond name (domain, company, or any handle). **How does the org β†’ team flow work?** Pass `domain: "acme.com"`. Scout enriches the domain (WHOIS / DNS / hosting / tech stack / cert transparency) and *also* fetches the team / about / leadership pages with a real browser (so React-rendered content lands in the DOM), strips `