Show HN: Evalyze – AI investor matching from your pitch deck (feedback welcome)
After sign-up (email only, no card) you can:
- upload a deck or paste your site - get a ranked list of relevant VCs/angels with a short “why” for each
What’s different: instead of dumping a big list, we try to explain why an investor fits based on stage, sector, check size, and portfolio patterns. It’s far from perfect and we want blunt feedback before opening wider.
Limits to know:
- newer funds and emerging managers can be underrepresented - geo nuances are still rough - matching can over-weight buzzwords if the deck is vague
I’d love critique on the ranking logic, signals you’d add/remove, and any privacy concerns. If you don’t want to upload a deck, there’s a sample you can use to see the flow.
I’ll be here replying and shipping fixes as comments come in.
Goal: relevance + reasoning, not mass-spray lists. If we can’t explain the match in plain language, we count it as a miss.
How it works (short): we extract signals from the deck/site (market, stage, traction hints), cross-match with investor theses and portfolios, then rank. LLM + rules handle the “why” section; we log failures to improve features/weights.
Stack: Next.js + FastAPI; Postgres + vector store; batch enrichment jobs for investor data.
Privacy: decks are stored only for processing; you can delete them from settings; logs don’t keep deck content.
Known gaps we’re fixing next: better geography weighting, fund recency signal, and negative-match cues (e.g., “consumer-only fund” should downrank B2B SaaS).
What would be most helpful:
- examples of bad matches and what we missed
- signals you’d trust (or not) in the “why” section
- anything confusing or heavy in the UI