GitHub & Engineering
Track engineering activity, open source engagement, and repository health across millions of companies with public GitHub presence.
Overview
GitHub signals surface engineering activity patterns—what companies are building, how fast they're growing, and where they're investing technically.
We crawl public GitHub activity and map organizations to company domains. We track repository-level metrics (stars, forks, commits) over 30/60/180-day windows. Signals fire when growth exceeds thresholds (>20% star growth in 90 days) or when patterns indicate strategic investment (new AI/ML repos, infrastructure tooling, platform ecosystem plays). Each signal aggregates metrics across the company's full GitHub portfolio, not just individual repos.
Available Subtypes
| Signal | Subtype Enum | Description |
|---|---|---|
| Rapid Growth | githubRapidGrowth | Repository experiencing fast star/fork growth (>20% in 90 days) |
| High Adoption | githubHighAdoption | High fork ratio indicates developers actively building on this project |
| New Project Traction | githubNewProjectTraction | New repository gaining significant early traction |
| Portfolio Momentum | githubPortfolioMomentum | Company's GitHub portfolio shows strong overall engineering velocity |
| Major OSS Player | githubMajorOSSPlayer | Company maintains flagship repositories (10k+ stars) |
| Enterprise Signal | githubEnterpriseSignal | Signals of enterprise-grade development (security, compliance, scale) |
| Platform Ecosystem | githubPlatformEcosystem | Company building a developer platform/ecosystem |
| AI/ML Investment | githubAIMLInvestment | Active investment in AI/ML repositories and tooling |
| Infrastructure Investment | githubInfraInvestment | Investment in infrastructure, DevOps, and cloud tooling |
| Developer Tooling | githubDeveloperTooling | Company maintains developer tools or SDKs |
| Open Source Investment | githubOpenSourceInvestment | Investment in open source projects |
Response Fields
Core Signal Fields
| Field | Type | Example | Description |
|---|---|---|---|
signal_id | string (UUID) | "a1b2c3d4-e5f6-7890-abcd-ef1234567890" | Unique identifier for this signal |
signal_type | string | "github-initiative" | Signal category |
signal_subtype | string | "githubAIMLInvestment" | Specific subtype enum |
detected_at | string (ISO 8601) | "2026-01-06T14:22:31.123456Z" | Timestamp when signal was detected |
batch_id | string | "gh-20260106-abc123" | Batch identifier for this signal run |
association | string | "company" | Association level (always "company" for this signal) |
Company Fields
| Field | Type | Example | Description |
|---|---|---|---|
company.name | string | "Stripe" | Company name |
company.domain | string | "stripe.com" | Company domain |
company.linkedin_url | string / null | null | LinkedIn company URL |
company.industries | array[string] | ["Financial Services", "Technology"] | Industry classifications |
company.description | string | "Stripe is a financial infrastructure platform..." | Company description |
Data Fields
| Field | Type | Example | Description |
|---|---|---|---|
data.summary | string | "Stripe launches AI agent toolkit for payments" | Short signal headline |
data.detail | string | "The stripe-agent-toolkit repository has grown 42%..." | Supporting detail with context |
data.relevance | float (0.0-1.0) | 0.83 | Business relevance score |
data.confidence | string | "high" | Confidence level: high, medium, low |
data.sentiment | string | "positive" | Sentiment: positive, neutral, negative |
data.referenced_repos | array[string] | ["stripe-agent-toolkit"] | Repositories referenced in the signal |
data.technologies_mentioned | array[string] | ["Python", "LLM", "AI Agents"] | Technologies mentioned in analysis |
Portfolio Metrics
| Field | Type | Example | Description |
|---|---|---|---|
data.portfolio_metrics.repository_count | integer | 40 | Total repositories in portfolio |
data.portfolio_metrics.growth.stars_pct.30d | float | 0.08 | Star growth percentage over 30 days |
data.portfolio_metrics.growth.stars_pct.60d | float | 0.13 | Star growth percentage over 60 days |
data.portfolio_metrics.growth.stars_pct.180d | float | 0.31 | Star growth percentage over 180 days |
data.portfolio_metrics.growth.forks_pct.30d | float | 0.06 | Fork growth percentage over 30 days |
data.portfolio_metrics.growth.forks_pct.60d | float | 0.11 | Fork growth percentage over 60 days |
data.portfolio_metrics.growth.forks_pct.180d | float | 0.29 | Fork growth percentage over 180 days |
data.portfolio_metrics.velocity.avg_stars_per_repo_30d | float | 34.2 | Average stars gained per repo in 30 days |
data.portfolio_metrics.concentration.top_3_star_share | float | 0.47 | Share of total stars held by top 3 repos |
Top Repositories
Each entry in data.top_repositories[] contains:
| Field | Type | Example | Description |
|---|---|---|---|
name | string | "stripe-agent-toolkit" | Repository name |
full_name | string | "stripe/stripe-agent-toolkit" | Full repository path |
url | string | "https://github.com/stripe/stripe-agent-toolkit" | GitHub URL |
description | string | "Python toolkit for building Stripe AI agents" | Repository description |
first_seen_at | string (ISO 8601) | "2024-11-11T17:13:41Z" | When repository was first detected |
current.stars | integer | 1184 | Current star count |
current.forks | integer | 181 | Current fork count |
current.watchers | integer | 1184 | Current watcher count |
growth_pct.stars.30d | float | 0.42 | Star growth percentage over 30 days |
growth_pct.stars.60d | float | 0.67 | Star growth percentage over 60 days |
growth_pct.stars.180d | float / null | null | Star growth percentage over 180 days (null if repo too new) |
growth_pct.forks.30d | float | 0.31 | Fork growth percentage over 30 days |
growth_pct.forks.60d | float | 0.52 | Fork growth percentage over 60 days |
growth_pct.forks.180d | float / null | null | Fork growth percentage over 180 days (null if repo too new) |
readme.text | string | "Build AI-powered payment experiences..." | README content (truncated) |
readme.source_url | string | "https://raw.githubusercontent.com/stripe/..." | README source URL |
Full JSON Response Example
{
"signal_id": "ea7688a5-d25c-475e-a60f-e84204b8c0b2",
"signal_type": "github-initiative",
"signal_subtype": "githubAIMLInvestment",
"detected_at": "2026-01-21T19:38:10.067Z",
"batch_id": "gh-20260121-89aa726e-c725-454d-8afc-4d5fb1e1984c",
"association": "company",
"company": {
"name": "0din",
"domain": "0din.ai",
"industries": [
"AI Security"
]
},
"data": {
"summary": "0din creates scoring framework to quantify AI jailbreak risks",
"detail": "The 0din-JEF repository introduces a Jailbreak Evaluation Framework to score LLM vulnerabilities, similar to CVSS for software exploits. This signals a deep investment in AI model security.",
"relevance": 0.82,
"confidence": "high",
"sentiment": "positive",
"referenced_repos": [
"0din-JEF",
"sidekick"
],
"technologies_mentioned": [
"Python",
"LLM",
"AI Security"
],
"portfolio_metrics": {
"repository_count": 3,
"growth": {
"stars_pct": {
"30d": 0.4,
"60d": 0.44,
"180d": 1.57
},
"forks_pct": {
"30d": 0.83,
"60d": 0.83,
"180d": 4.5
}
},
"velocity": {
"avg_stars_per_repo_30d": 5.7
}
},
"top_repositories": [
{
"name": "0Din-Curated-Monthly-White-Papers",
"full_name": "0din-ai/0Din-Curated-Monthly-White-Papers",
"url": "https://github.com/0din-ai/0Din-Curated-Monthly-White-Papers",
"description": "Curated collection of monthly white papers focused on LLM attack and defenses.",
"current": {
"stars": 26,
"forks": 2,
"watchers": 7
},
"growth_pct": {
"stars": {
"30d": 0,
"60d": 0.04,
"180d": 0.13
}
}
}
]
}
}API Usage
Generate Content API
{
"enabledInsights": ["githubRapidGrowth", "githubHighAdoption", "githubInfraInvestment"],
"disabledInsights": []
}Generate Insights API
{
"contactCompanyUrl": "stripe.com",
"insightSubtype": "githubAIMLInvestment"
}Example Output
"Noticed Stripe's engineering team just launched an AI agent toolkit—their stripe-agent-toolkit repo has grown 42% in the last month with over 1,100 stars. With that level of investment in AI-powered payment experiences, ensuring your AI integrations are reliable and well-monitored becomes critical. Would love to share how we help teams building AI-first products."
Coverage
- Refresh: Weekly
- Coverage: 1-25% of companies (requires public GitHub presence)
- Best for: Developer tools, DevOps, technical recruiting, infrastructure sales
Updated 2 days ago
