Social Intelligence

GitHub Activity Signals

Portfolio-level engineering signals from public GitHub activity: AI/ML investment, developer tooling, infrastructure scaling, security focus, and more. Roughly 250,000 signals a month across 86,000+ companies.

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15M+

Companies Covered

Signal Subtypes

Weekly

Refresh Cadence

Stars, Forks, Languages

Metrics Tracked

Social Intelligence11 subtypes · Weekly refresh

What Are GitHub Activity Signals?

GitHub activity signals track what a company's engineering team is building, measured across its entire public repository portfolio rather than individual repos. Autobound maps GitHub organizations to company domains for 15M+ companies and fires a signal when activity crosses meaningful thresholds: star growth above 20% in 90 days, a cluster of new AI/ML repositories, or sustained investment in infrastructure and security tooling.

Subtypes cover AI/ML investment, developer tooling, open-source investment, infrastructure scaling, security focus, and new project launches. Each signal carries portfolio metrics: repository count, star and fork growth over 30, 60, and 180 days, top repositories, and the technologies involved. At roughly 250,000 signals a month across 86,000+ companies, this is observable engineering behavior, visible before any buying process starts.

Example Signal Subtypes

githubAIMLInvestmentgithubDeveloperToolinggithubOpenSourceInvestmentgithubInfrastructureScalinggithubNewProjectLaunchgithubSecurityFocusgithubMobileDevelopmentgithubRapidGrowth

Data Schema

GitHub Signal Data Schema

GitHub signals include portfolio-level metrics, repository trends, technology categorization, and growth velocity measurements.

github_activity.schema.json

{
  "signal_id": "c9d34e56-7b2a-4f19-8c83-1e5d9f0a2b67",
  "signal_type": "github-initiative",
  "signal_subtype": "githubAIMLInvestment",
  "detected_at": "2026-07-14T09: 22: 31Z",
  "batch_id": "gh-20260714-89aa726e-c725-454d-8afc-4d5fb1e1984c",
  "association": "company",
  "company": {
    "name": "Vercel",
    "domain": "vercel.com",  // match on domain
    "linkedin_url": "linkedin.com/company/vercel",  // or match on LinkedIn URL
    "industries": ["Developer Tools", "Cloud Infrastructure"],
    "description": "Frontend cloud platform for AI-native web applications..."
  },
  "contact": [],
  "data": {
    "summary": "Vercel's AI SDK repo grows 34% in 180 days as the company deepens its AI tooling investment",
    "detail": "The ai repository (Vercel AI SDK) added 3,400 stars over the past 90 days, driven by adoption of streaming and agent patterns in production apps. Combined with two new inference-related repos, this signals sustained AI/ML investment across the portfolio...",
    "relevance": 0.87,
    "confidence": "high",
    "sentiment": "positive",
    "referenced_repos": ["ai", "next.js"],
    "technologies_mentioned": ["TypeScript", "LLM streaming", "React Server Components"],
    "portfolio_metrics": {
      "repository_count": 142,
      "growth": {
        "stars_pct": { "30d": 0.06, "60d": 0.14, "180d": 0.31 },
        "forks_pct": { "30d": 0.05, "60d": 0.11, "180d": 0.24 }
      },
      "velocity": { "avg_stars_per_repo_30d": 41.7 },
      "concentration": { "top_3_star_share": 0.52 }
    },
    "top_repositories": [
      {
        "name": "ai",
        "full_name": "vercel/ai",
        "url": "https://github.com/vercel/ai",
        "description": "The AI Toolkit for TypeScript, for building AI-powered applications",
        "first_seen_at": "2023-05-25T17: 13: 41Z",
        "current": { "stars": 16800, "forks": 2900, "watchers": 16800 },
        "growth_pct": {
          "stars": { "30d": 0.09, "60d": 0.19, "180d": 0.34 },
          "forks": { "30d": 0.07, "60d": 0.15, "180d": 0.28 }
        }
      }
    ]
  }
}

GCS Bucket: gs://autobound-github-v1/
Formats: JSONL · Parquet
Refresh: Weekly

Full schema docs →Measured coverage →

Applications

What teams build with GitHub Activity Signals

04 documented applications

01
Developer Tool Sales
Identify companies whose engineering teams are actively building with technologies your product supports. GitHub activity reveals technology adoption before any official procurement process begins.
02
Cloud Platform Partnerships
Track companies with growing open-source portfolios that could benefit from cloud infrastructure partnerships. Repository growth and star velocity indicate expanding engineering operations.
03
AI/ML Investment Detection
Detect companies investing in AI and machine learning by tracking ML framework usage, model repository creation, and data pipeline tooling in their GitHub portfolios.
04
DevOps and Infrastructure Sales
Monitor for companies adopting containerization, orchestration, and CI/CD tooling in their repositories. These adoption patterns indicate infrastructure modernization initiatives.

Measured, Not Estimated

What's actually inside GitHub Activity Signals

Volumes, subtypes, geography, and join-key fill rates audited directly from our production database, so you can verify coverage before you buy.

Measured coverageaudited from production · minimums, not ceilingsEmerging source

86,406

companies with fresh data / month

basis: 3-mo avg

249,170

records created / month

basis: 30-day window

Top subtypes

14 total

Github Developer Tooling563K · 37%

Github Open Source Investment361K · 24%

Github Infrastructure Scaling163K · 11%

Github AIMLInvestment135K · 8.9%

Github New Project Launch132K · 8.6%

Github Security Focus76K · 4.9%

Github Mobile Development53K · 3.5%

Github Rapid Growth43K · 2.8%

Geography

all 134 countries →

🇺🇸United States2.8K · 3.1%

🇩🇪Germany734 · 0.8%

🇬🇧United Kingdom653 · 0.7%

🇫🇷France497 · 0.5%

🇮🇳India485 · 0.5%

🇨🇦Canada344 · 0.4%

🇳🇱Netherlands326 · 0.4%

CA 1.5KNY 489TX 256MA 184WA 143FL 140

Top industries

all industries →

Software Development2.3K · 2.5%

IT Services and IT Consulting830 · 0.9%

Technology, Information and Internet590 · 0.6%

Information Technology & Services346 · 0.4%

Computer and Network Security242 · 0.3%

Blockchain Services234 · 0.3%

Computers and Electronics Manufacturing234 · 0.3%

Join keys

fill rate

Domain100%

LinkedIn URL3%

Company name93%

Records measured 1,527,099+Companies reached 91,105+Full schema & examples →

See the real records for yourself.

See full coverage & segmentation across all 35 signal types →

Worked Example

One signal, traced to outcome

One GitHub Activity Signals record followed from detection, through the action a rep took on it, to the measured result. Illustrative composite of observed customer workflows.

01 signal → 02 action → 03 outcome

Signal detected

Vercel's GitHub organization shows a surge in AI-related repositories, with 3 new ML inference repos in 60 days, plus their Next.js star count jumping 8% to 132K. The 'aiMlInvestment' signal fires.

Action taken

An AI infrastructure vendor reaches out to Vercel's CTO:

“Your GitHub activity shows a clear bet on AI-native web apps, with 3 new ML repos this quarter. We power the inference layer for companies making exactly this transition. Worth 15 minutes?”

Outcome

Technical deep-dive scheduled

Because the outreach was grounded in observable engineering activity, not marketing press releases.

Run this against live data →

FAQ

Frequently Asked Questions

What makes GitHub activity signals different from other intent data?

GitHub signals reveal engineering investment at the portfolio level, including which technologies a company is building with, how fast their developer ecosystem is growing, and where they're investing R&D resources. This is observable behavior, not self-reported data.

How many companies have GitHub activity signals?

Our GitHub signal coverage spans 50M+ companies, making it one of our broadest datasets. We track organizational GitHub accounts, repository activity, star growth, fork velocity, and new project launches.

What are the 11 GitHub signal subtypes?

The subtypes include AI/ML investment, developer tooling, platform ecosystem, infrastructure modernization, open-source velocity, star growth surge, compliance programs, security tooling, API development, developer community, and fork activity.

Can I detect when a company starts investing in AI or ML?

Yes. The aiMlInvestment subtype specifically detects when companies create new AI/ML-related repositories, adopt ML frameworks, or show increasing activity in AI-adjacent projects. This is a strong signal for AI infrastructure and tooling vendors.

How It Works

From Raw Data to Your Stack

Autobound ingests from LinkedIn API, Glassdoor, GitHub, Reddit, G2, extracts structured signals with AI, and delivers them however your infrastructure needs.

Autobound Ingests

Raw data from LinkedIn API, Glassdoor, GitHub, Reddit, G2 is continuously collected and normalized across millions of sources.

AI Extracts & Scores

ML models extract 11 signal subtypes with relevance scoring, confidence levels, and entity resolution.

You Receive

Structured JSONL delivered via your preferred method, updated on a weekly cadence.

REST API

Real-time access with subtype filtering

300 req/min

GCS Push

Automated delivery to your bucket

JSONL + Parquet

Enrich API

On-demand LLM-ranked insights

AI relevance scoring

Flat File

Bulk exports for data warehouses

CSV, JSON, Parquet

3 vendors consolidated

“By consolidating three data vendors into Autobound's Enrich API, we added 100+ new signal types and saved 4 months of engineering time.”

AiSDR Team

Engineering, AiSDR

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