How we collect, verify, and publish AI company signals.
Last reviewed: April 2026
AI-Buzz tracks package downloads, code adoption, contributor activity, hiring demand, and funding across AI companies. Most signals sync daily at 6 AM UTC. Funding data is manually verified before publication.
We focus on developer adoption signals — what developers are actually using in production — not just who raised funding. Not every signal movement becomes a published claim. Research Briefs are published only when changes survive anomaly checks.
We don't index every company with an AI landing page. A company qualifies when it has:
Package mappings and company identity are reviewed before a profile goes public. Inclusion does not imply endorsement or market leadership — it means we found enough public evidence to track the company consistently.
AI drafts each brief from structured company metrics. A human editor selects the question, verifies the figures, and approves the claim before publication. Each brief carries a disclosure stating this process.
If interpretation changes due to new data, we update the brief with a revision note and new as-of date — the original claim is not silently changed.
| Signal | Source | What's Measured | Frequency |
|---|---|---|---|
| Package Downloads | npm, PyPI | Daily download counts per tool, summed into 30-day totals with month-over-month trends. Multi-package companies aggregate across all tools. | Daily |
| GitHub Activity | GitHub API | Stars, forks, and growth trends | Daily |
| GitHub Contributors | GitHub API | Unique commit authors in last 30 days across all company repos | Daily |
| npm/PyPI Dependents | Libraries.io | Count of packages that depend on company npm/PyPI packages | Weekly |
| Code Adoption | ecosyste.ms | Public repositories importing company packages (dependent repo count) | Daily |
| HN Mentions & Sentiment | HN API | 30-day mention counts, discussion share by category. Sentiment classified by Gemini LLM (positive / neutral / negative, ~80% accuracy). Only shown when sample size >= 25 comments. | Daily |
| Reddit Mentions & Sentiment | Reddit Search API | 30-day mention counts in ML subreddits (r/MachineLearning, r/LocalLLaMA, r/artificial). Sentiment classified by Gemini LLM. | Weekly |
| Job Demand | HN API | Company mentions in monthly HN hiring threads. Skews toward startup/tech roles. | Monthly |
| Docker Hub Pulls | Docker Hub | Container adoption | Weekly |
| Hugging Face Downloads | Hugging Face | ML model adoption | Weekly |
| Hugging Face Models | Hugging Face | ML model portfolio breadth | Weekly |
| Funding | TechCrunch, VentureBeat, Wikipedia | Round size, type, date, lead investors | As announced, manually verified |
| Company News | TechCrunch, VentureBeat, major tech publications | News articles tracked per company from major tech publications | Daily |
Each company gets a confidence score based on profile completeness, identifier verification, metric freshness, and signal coverage. Scores below 40 mean significant data gaps — treat conclusions with caution.
Funding rounds are detected from news feeds and cross-referenced against company announcements. Every round is manually verified before appearing on a profile.
Factual errors are corrected visibly. Research Brief interpretation changes get a revision note and new as-of date. Use the "Report an error" button on any company profile, or email nick@ai-buzz.com.
AI-Buzz data is citable when the page URL and retrieval date are preserved.
Composite score (0–100) combining 4 adoption signals. All inputs are external and independently verifiable. See the DAI page for the leaderboard.
DAI = Σ (weighti × normalize(signali)) × 100| Component | Weight | Source |
|---|---|---|
| Package Downloads | 40% | npm, PyPI (30-day totals) |
| Download Growth | 25% | Month-over-month trend |
| Dependents | 20% | Libraries.io, npm registry |
| GitHub Contributors | 15% | Unique contributors in 30 days |
Each signal is normalized using percentile ranking across non-zero values. Download growth uses trend normalization (-200% → 0, 0% → 0.5, +200% → 1.0). Scores recompute daily after syncs; computation aborts if >10% of companies have stale data.
Measures how quickly a company is gaining or losing developer traction (0–100). Six directional components, v2 weights since March 2026:
| Component | Weight |
|---|---|
| HN mentions trend | 20% |
| GitHub stars trend | 20% |
| Download trend | 20% |
| Funding recency | 15% |
| Code adoption | 15% |
| Job demand | 10% |
When components are missing, available weights redistribute proportionally. A confidence value records the fraction present (1.0 = all 6).
Weight changes are also logged to the public changelog feed.
Simplified from 9 to 4 verified adoption signals. Removed sentiment proxies, lagging indicators. Renamed to Developer Adoption Index (DAI).
Removed self-referential signals (page views, GSC impressions). All 9 signals external.
Added demand-side signals. Later removed in v3.0 due to circularity.
Original signal score with equal weighting across HN mentions, GitHub stars, funding, and downloads.