GitHub Identity Resolution

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What GitHub identity resolution is

GitHub identity resolution is the process of mapping a GitHub username to a verified professional identity — LinkedIn profile, current employer, title, and work email — with high precision.

It’s the technical answer to a common GTM problem: you have developer signals (stars, forks, PRs, issues) but you don’t know who the humans are behind them.

The LeadCognition approach: multi-stage identity validation

Most enrichment APIs run name matching against a database. LeadCognition runs identity confirmation.

The difference: a name match finds a LinkedIn profile that could be the right person. Identity confirmation validates it IS the right person.

Stage 1 — Signal extraction

Extract all available identity signals from the GitHub profile: username structure, display name, bio text, company field, location, linked URLs, commit email patterns (without requiring a public email), language stack, contribution graph shape.

Stage 2 — Candidate resolution

Cross-reference extracted signals against enrichment databases to surface LinkedIn profile candidates. Signals are weighted by reliability — company mention outweighs location; commit email pattern outweighs bio text.

Stage 3 — Identity confirmation

Validate each candidate against:

• Career trajectory (does their professional history make sense for their GitHub activity?)
• Professional context (does their industry match their technology stack?)
• Industry signals (are they a developer, or a politician/lawyer/journalist who happens to share a name?)

Same-name collisions — the core failure mode of naive resolvers — are eliminated at this stage.

If confidence falls below threshold: no result returned, no charge.

Why same-name collision engineering matters

Consider a GitHub user @alexjohnson. Naive name matching might return a LinkedIn profile for “Alex Johnson, Personal Injury Lawyer.” Sending an outbound email about your DevTool API to a lawyer is worse than not sending anything — it damages your brand and wastes your SDR’s time.

LeadCognition’s career trajectory and industry signal validation catches these collisions. A lawyer named Alex Johnson will not have a TypeScript-heavy commit history. A developer named Alex Johnson working at a fintech startup won’t have a political consulting background on LinkedIn.

This is why our precision is 90%+ — not 60% like naive enrichment APIs.

API

POST /api/v1/deanon
Authorization: Bearer {api_key}

{
  "githubUsername": "torvalds",
  "includeEmail": true
}

Response:

{
  "resolved": true,
  "confidence": 0.97,
  "linkedin": "https://linkedin.com/in/...",
  "name": "...",
  "title": "...",
  "employer": "...",
  "workEmail": "...",
  "credits_charged": 3
}

Full API docs →

Pricing

Free tier: 50 credits, no credit card required.

See pricing → Start Free →

Use cases

GitHub signal → outbound contact — Every new star/fork on your repo triggers identity resolution. Enriched contact with LinkedIn + email lands in your CRM automatically.

Stargazer list enrichment — Upload your historical GitHub stargazer list. Resolve identities in batch. Turn 3 years of GitHub signals into a prioritized outbound queue.

Contributor profiling — Identify the professional identities of open-source contributors in your category. Know who’s building in your space before they reach out to you.

ICP scoring — After resolution, score the developer against your ICP: company size, industry, title seniority, tech stack. Filter for qualified leads before any outreach.

Frequently Asked Questions