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For Due diligence analysts
Verify engineering claims with public data instead of taking the founder's word.
Technical due diligence in venture historically depended on founder self-reporting plus a partner's intuition about the team. Public engineering data has changed that — diligence teams can now verify shipping pace, contributor growth, language stack, and architectural choices independently, in hours rather than weeks. VC Deal Flow Signal is the structured layer most diligence teams use as the first pass.
Diligence time
30 min vs week+ manual
Cost vs technical consultant
EUR 9.97/mo vs $5-15K
Verification depth
Full historical metrics
Problem
Founder pitch decks describe shipping velocity and team composition; diligence teams rarely have time to independently verify these claims. Bringing in a technical advisor to spend a week reviewing a startup's GitHub org costs four-figure consulting fees and weeks of latency. For most checks the diligence team accepts the founder's framing, which can produce expensive surprises post-investment.
How VC Deal Flow Signal fits
VC Deal Flow Signal provides instant access to historical engineering metrics for any startup with a public GitHub footprint. Verify the founder's velocity claims, benchmark against sector peers at the same stage, identify any concerning patterns (declining contributor counts, fork-and-rename artifacts, single-contributor dependencies). The diligence pass that previously took a week takes 30 minutes.
Most venture-backed technical companies are already in the panel. Pull the company's full historical chart with one search.
Compare the founder's described shipping pace to the actual commit velocity over the same period. Material discrepancies merit follow-up questions.
Look for healthy contributor distribution (multiple contributors, sustained over time) versus concentration risks (single contributor responsible for 80%+ of recent commits).
Use the sector pages to compare the target's metrics against companies at the same stage in the same sector. Top quartile, bottom quartile, or middle of the pack.
Reference the source data in the diligence memo. The methodology is published openly, so partners and IC members can verify the diligence work themselves.
No, it complements one. Engineering acceleration provides quantitative metrics; a technical advisor provides architectural and code-quality judgment. For checks above $1M most diligence teams use both.
The signal works for any startup with at least some public engineering footprint — public SDK, infra repos, OSS components. For purely closed-source companies, the diligence layer requires alternative sources. Many SaaS companies have at least some public artifacts.
Yes. The data is public, so sharing diligence findings with the founder during follow-up conversations is appropriate. Many founders welcome the structured metrics — it gives them a defensible answer to investor velocity questions.