Disclosure up front: I built the project this dataset backs, and I am sharing the raw data here because it is genuinely useful for anyone mining founder or engineering signals.<\/p>\n
This is Q3 2026 engineering momentum across 350+ startup GitHub organizations in 15 sectors (web3, data infrastructure, enterprise SaaS, robotics, healthcare, legal tech, space tech, and more). Updated weekly.<\/p>\n
What is inside, per org: – 14-day commit velocity and velocity change % – contributor count and growth – new-repo creation – a signal label (engineering hiring burst \/ deploy frequency spike \/ infrastructure buildout \/ framework migration) – funding stage estimate (pre-seed through growth) and geography<\/p>\n
Collected from public GitHub events only. No private repositories.<\/p>\n
The research finding this backs: in a panel of 219 confirmed fundraises (SSRN preprint), a composite of commit velocity and contributor diversity preceded fundraise announcements by 21 to 47 days (median 31), a 3.4x lift over baseline. The methodology page has the full definition; the preprint is at papers.ssrn.com, abstract 6606558.<\/p>\n
Get the data (free, no API key): – JSON: signals.gitdealflow.com\/api\/signals.json – Catalog with CSV + JSON exports and field docs: gitdealflow.com\/datasets – Methodology: signals.gitdealflow.com\/methodology<\/p>\n
License: CC BY 4.0 (attribute as ‘Source: GitDealFlow, CC BY 4.0’).<\/p>\n
One caveat worth knowing: velocity-change % saturates at +999% on the biggest jumps, so for top movers rely on the absolute commit counts rather than the percentage.<\/p>\n
Happy to answer questions about the pipeline or the caveats.<\/p>\n<\/div>\n
submitted by \/u\/Worth_Wealth_6811 <\/a>
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