Semantic search engine for finding relevant VCs and angels
We built a search engine that matches startup descriptions with investors based on their historical investments. Write your startup description and get a list of investors who've backed similar companies. Technical implementation: - Indexed 9k active VC funds and ~5k angels globally - Fine-tuned a custom embedding model on real-world pairs of investors and companies - Developed an identity resolution system to collate portfolio data across many sources including portfolio websites scraped with a custom AI agent Key features: - Search full investor database without signing up - Optional…
In plain words
This semantic search engine helps startups find relevant investors by matching their company description against 9,000 VC funds and 5,000 angels worldwide. Users describe their startup and receive a ranked list of investors who have backed similar companies, based on a custom embedding model trained on real investor-company pairs. The tool searches the full investor database without requiring signup and optionally integrates email and calendar data to show connection degrees to prospects.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
We built a search engine that matches startup descriptions with investors based on their historical investments. Write your startup description and get a list of investors who've backed similar companies. Technical implementation: - Indexed 9k active VC funds and ~5k angels globally - Fine-tuned a custom embedding model on real-world pairs of investors and companies - Developed an identity resolution system to collate portfolio data across many sources including portfolio websites scraped with a custom AI agent Key features: - Search full investor database without signing up - Optional email/calendar integration shows 1st/2nd degree connections to investors - Results ranked by semantic similarity to historical investments Example query: "B2B SaaS platform for automating accounts payable workflows using OCR and ML" → Returns VCs/angels who've invested in similar enterprise automation/fintech companies Origin: Built this after struggling with my own seed round. Existing solutions didn't solve the core problem: systematically finding ALL relevant investors, not just the obvious ones. Would appreciate feedback on: 1. Search result quality/relevance 2. Additional data points that would be useful 3. Performance/latency issues if you encounter any Team: danishabdullah, combdn, thelifeofrishi, howes, Hossamhamdy20, Isomorpheus
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