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Q2 2026 · Series A / Series B · Data Infrastructure
1 data infrastructure startups at series a / series b stage ranked by GitHub engineering acceleration in Q2 2026. starlake-ai leads with 83 commits over 14 days (-35%). Growth-stage technical startups that have closed institutional rounds. Engineering signals at this stage are less about discovery and more about validation of trajectory.
Investor insight
At Series A/B, engineering acceleration is a trajectory signal rather than a discovery signal. A hiring burst or platform buildout often precedes the next round. Institutional investors use these signals to prioritize outreach and refine conviction before a lead term sheet.
| # | Company | Stage | Geo | Commits (14d) | Change | Contributors | Contrib. Growth | New Repos | Signal |
|---|---|---|---|---|---|---|---|---|---|
| 1 | starlake-aiView signal profile → | Series A/B | EU | 83 | -35% | 29 | +184% | 0 | Engineering hiring burst |
Sorted by commit velocity change (14-day window). Stage from contributor count + enrichment. Last updated Q2 2026.
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starlake-ai leads data infrastructure series a / series b-stage startups in Q2 2026 with 83 commits over a rolling 14-day window (-35% change) and 29 active contributors. Across all 1 data infrastructure startups at this stage, the average 14-day commit velocity is 83 commits.
At Series A/B, engineering acceleration is a trajectory signal rather than a discovery signal. A hiring burst or platform buildout often precedes the next round. Institutional investors use these signals to prioritize outreach and refine conviction before a lead term sheet.
Stage is derived from contributor count, team-size enrichment, and funding history where publicly available. Stage buckets (Pre-Seed, Seed, Series A/B, Growth) use broad matching for sample size. Always verify independently before any investment action.