Loading...
For Fund of funds / LPs
Benchmark your VCs' sourcing quality against a common engineering signal, and spot emerging GPs with better deal flow before everyone else does.
Most LPs evaluate a VC's sourcing by looking at deployed deals — a lagging indicator that takes years to mature. VC Deal Flow Signal gives LPs and fund of funds a new kind of leading indicator: how do the companies a GP backed compare to the companies VC Deal Flow Signal flagged at the same moment? And for emerging managers — which of them are consistently getting into companies that later show up as breakout engineering signals?
Historical archive depth
Growing weekly since Q1 2026
Sectors covered
20 technical clusters
Data accessibility
JSON / CSV / MCP / RSS
Benchmark cost
EUR 9.97/mo (beta)
Problem
Sourcing quality is hard to measure from the outside. LPs rely on GP self-reporting, which is flattering by construction, or on IRR / DPI, which are 7-10 year signals. There is no industry benchmark for 'would a reasonable engineering-signal tool have flagged this startup at the same time?' that LPs can apply consistently across their portfolio of GPs.
How VC Deal Flow Signal fits
Use VC Deal Flow Signal's weekly dataset as a benchmark. For each portfolio company a GP invests in, check whether that company was flagged as a breakout engineering signal 6-12 weeks before the round — and if so, whether the GP was already engaged. GPs whose wins correlate strongly with leading engineering signals are likely sourcing on the early side. GPs whose wins correlate with no early signal are either backing non-technical companies, or sourcing through networks that the signal does not capture.
Past periods are accessible via the data API and archived sector pages. For any date range, you can pull the full list of startups that were flagged as breakout engineering signals.
For each GP-backed company, check whether VC Deal Flow Signal flagged it in the 6-12 week window before the round. Build a score: how often does this GP's pipeline overlap with the leading signal?
The overlap score is not a quality metric on its own — non-technical funds will score low for structural reasons — but across a peer group of technical-sector GPs, it is a useful sourcing-speed proxy.
For emerging GPs you are considering, ask for their recent pipeline and run the same overlap score retroactively. A new GP whose sourcing tracks an independent engineering signal is validating their thesis with an external benchmark.
When a GP pitches a sector thesis, check how many companies VC Deal Flow Signal flagged in that sector over the past year. If the thesis is 'AI infrastructure is hot', the signal archive tells you whether that was true 6 months earlier in engineering activity.
Yes — email signal@gitdealflow.com with the date range and sector focus. The beta tier access includes custom exports for LP use cases on request.
The signal only covers technical startups with public GitHub activity. For consumer, healthtech, or services GPs, the overlap score is structurally low and not meaningful. Use the signal only for peer groups where the sector mix is comparable.
The signal measures any public GitHub activity — both open-source projects and companies with public infrastructure repos, public API repos, or public SDKs. It is biased toward technical startups that do any of their engineering work in public, which is the majority of modern SaaS and dev tools but a minority of closed-source B2B.
Yes. The data is available in machine-readable formats; email signal@gitdealflow.com for scoped help building a custom benchmark or GP scoring model. The product team is small but direct.