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Current Signal — Q2 2026
starlake-ai shows -35% commit velocity change with 29 active contributors (+184% growth). Signal type: Engineering hiring burst. Trend vs. prior quarter: decelerating (was +67% in Q1 2026).
Data sourced from public GitHub activity. Read our methodology
Commit Velocity (14d)
83
Velocity Change
-35%
Contributors
29
+184% growth
New Repos (30d)
0
| Period | Velocity (14d) | Change | Contributors | Growth | New Repos | Signal |
|---|---|---|---|---|---|---|
| Q2 2026 | 83 | -35% | 29 | +184% | 0 | Engineering hiring burst |
| Q1 2026 | 20 | +67% | 29 | +184% | 0 | Engineering hiring burst |
| Q4 2025 | 39 | -22% | 29 | +184% | 0 | Engineering hiring burst |
| Q3 2025 | 16 | -80% | 29 | +184% | 0 | Engineering hiring burst |
starlake-ai's contributor count is growing at +184%, which classifies as an engineering hiring burst. This pattern typically means the company has recently closed a funding round and is rapidly scaling its engineering team.
If you are seeing this signal, you may be too late for the current round but well-positioned for the next one. The team expansion suggests the company has capital to deploy and is building toward a product milestone.
As of Q2 2026, starlake-ai shows a "Engineering hiring burst" signal with -35% commit velocity change over a 14-day window, 29 active contributors, and +184% contributor growth. This indicates rapid team expansion, often following a funding round.
VC Deal Flow Signal does not predict specific funding rounds. However, starlake-ai's engineering acceleration pattern (-35% commit velocity change in Q2 2026) is the type of signal that has historically preceded fundraise announcements by three to six weeks. Investors should cross-reference this signal with other sources (Crunchbase, hiring activity, community mentions) before drawing conclusions.
starlake-ai is tracked in our Data Infrastructure sector rankings for Q2 2026. View the full sector ranking at signals.gitdealflow.com/startups-to-watch/data-infrastructure-q2-2026 to see how it compares on commit velocity, contributor count, and signal type against other data infrastructure startups.
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