score-vc-fit

Rank venture capital funds by scoring each candidate against your startup's fundraising brief using an 8-dimension rubric covering sector, stage, geography, check size, lead behavior, portfolio adjacency, recency, and partner relevance to produce a prioritized outreach list.

Scoring VC fit with missing evidence yields null scores for those dimensions and flags the result as low-confidence, allowing you to proceed with ranking while identifying gaps in your fund candidate data for further diligence.

Generate a prioritized outreach list by processing your company profile and fund candidates through an 8-dimension rubric, merging investor contacts, and sorting results by score_total descending into a structured scored_funds.json file.

You can compute an optimized warm introduction order by running your fundraising brief data and fund candidates through the scoring rubric, which merges investor contacts and outputs a ranked list sorted by total fit score.

VC fit is evaluated across eight dimensions: sector, stage, geography, check size, lead behavior, portfolio adjacency, recency, and partner relevance, with each fund scored out of 100 based on alignment with your fundraising brief.

You need normalized company profile data, raw fund candidates, and normalized investor contacts as inputs, since the scoring rubric reads these files to evaluate fund fit and generate the ranked scored_funds output.