AI Recommendations
Surface the best-fit option — a product, a match, a listing — ranked by what actually matters to the person looking, not just the newest or most-viewed.
Good recommendations feel obvious in hindsight and are quietly difficult to build. We score candidates against the criteria your users actually care about — not just filters like price or category, but the softer signals that separate a decent match from the right one.
This is the same engine behind matching platforms, buyer-listing tools and product recommendation widgets — the pattern transfers cleanly across industries with the scoring logic tuned to your data.
Scoring logic is built around what you tell us actually correlates with a good match in your data — a purchase, a saved listing, a completed enquiry — rather than a one-size-fits-all popularity ranking that just resurfaces the same handful of items to everyone.
We also account for cold-start cases: new products, new listings, and new users with no history yet still need a sensible ranking on day one, not a blank slate until enough data accumulates.
Where recommendations apply
Matching & Compatibility
Score candidates on real criteria, not just filters like price or category.
Product Recommendations
Surface the items most relevant to each user, tuned to your catalog.
Ranked in Real Time
Results reorder instantly as new data or preferences come in.