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The Universal Matching Engine.

Founders to investors. People to products. Partners for dating. One engine for every match that matters.

We learn deep representations of people and intent, then match users with the most compatible person or product in the set.

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Vectors Indexed
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Expert Reviewed Matches
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Vector Latency (ms)
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AUC — Compatibility Prediction
Briefing

How We Match.

Platform

The Universal Matching Engine

One platform for every match that matters. Founders to investors, candidates to roles, partners for dating. Domain-specific embeddings and rerankers trained on the outcomes you care about.

Can AI Match Founders to the Right Investors?

We gave every major embedding model the same task: given a founder and an investor, predict whether experienced VCs would rate them as a strong match. Higher on both axes = better.

Spearman ρ
0.000.100.200.300.40
Random chance (0.50)
Gemini(0.49, 0.05)
OpenAI(0.51, 0.08)
Jina(0.50, 0.07)
Qwen(0.52, 0.10)
Voyage(0.54, 0.12)
Jean Embeddings(0.63, 0.28)
Jean Reranker(0.71, 0.40)
0.450.500.550.600.650.700.75
AUC
Random chance (0.50)AUC = prediction accuracySpearman ρ = ranking agreement with VCs
Core Product

Person Search

We train custom embedding models on expert-labeled data. The model learns what “good match” means in your specific domain.

Hires that stay. Matches that convert. Connections that compound. Standard embeddings reward keyword overlap. Ours reward compatibility.

Recruiting & Hiring

Rank candidates by predicted tenure and performance, not resume keywords.

Dating & Social

Match on behavioral compatibility and relationship success signals.

Marketplace Matching

Connect buyers to sellers, mentors to mentees, founders to investors. Optimized for conversion.

Ready to build?

We deploy custom infrastructure tailored to your domain.