Preference signals
Turning intent, context, and constraints into cleaner matching inputs.
Algorithms for better introductions
Inner Product is building matching models that learn from real preferences, social context, and reciprocal fit.
Turning intent, context, and constraints into cleaner matching inputs.
Looking for matches that make sense from both sides, not only one ranking.
Optimizing for better introductions, conversations, and follow-through.