Inbound deal scoring is the practice of rating startups that come to a fund on their own, through warm intros, referrals, cold email, or a form on the website, against the fund's thesis and bar. Each company gets a ranked, evidence-backed score instead of a partner's read from a five-minute deck skim.
Every fund's inbound queue looks the same: a mix of strong founders who don't have a warm path in, recycled decks that already got passed on twice, and the occasional outlier that turns into the best deal of the year. Inbound deal scoring runs a consistent rubric across all of it. The deck, the founder's background, and any public signal get pulled together, checked against the fund's stated thesis, and turned into a score with the supporting evidence attached, similar to how founder scoring rates the people rather than the pitch.
In practice this means every inbound company lands on the same rubric on dimensions like:
The volume problem in inbound is real and getting worse as more founders default to cold outreach over warm intros. A recent breakdown of AI-assisted deal triage found that when a model reads every inbound deck, scores it against the fund's documented thesis, and produces a one-page brief, time per deal for the reviewing partner drops from about 45 minutes to 8 minutes, cutting partner hours on inbound triage by 60 to 80 percent when the thesis is well documented. Affinity's 2026 survey of nearly 300 private capital dealmakers found the shift is already mainstream: 85 percent now use AI to automate daily tasks, up from 76 percent a year earlier.
None of that matters if the scoring is a black box. A partner who can't see why a company scored a 7 won't trust the 7. That's the case for evidence-backed scoring specifically: every score should point back to the line in the deck, the GitHub commit, or the customer reference that produced it, the same way we describe it in evidence-based scoring.
Inbound and outbound are different problems wearing the same word, "deal flow." Outbound, covered under deal sourcing, is about finding companies the fund doesn't yet know exist. Inbound scoring assumes the company already found you, so the job is triage, not discovery: rank what's already in the queue fast enough that a great founder doesn't sit unread for two weeks. Funds that treat both with the same manual process end up either drowning in inbound or starving their outbound pipeline. See how Henri breaks down the actual scorecard we run on every inbound founder in the diligence scorecard we run on every inbound founder.
No. It replaces the manual first pass. The partner still decides, but they open the memo with a ranked list and the evidence behind every score instead of a stack of unread decks.
The deck itself, public founder history, any traction data the company shares, and how closely the pitch matches the fund's stated thesis. Over time a fund's own pass/win history can calibrate the weights.
A pipeline stage tells you where a deal sits. A score tells you why it's there and whether it deserves a partner's time next, with the reasoning attached rather than a tag someone applied from memory.
Send us your next batch of inbound founders. We'll rank them against your thesis, live, with the receipts behind every score.