AI-Powered Search
Semantic search that understands intent, not just keyword matches — built for large or unstructured content sets.
Keyword search works fine until your content is large, varied, or described inconsistently. AI-powered search using vector embeddings and hybrid retrieval lets users search by intent — a listing described as "quiet, near transit, pet-friendly" rather than a rigid set of filter checkboxes — and still returns relevant results when the exact words don't match.
We typically combine semantic search with traditional filtering rather than replacing one with the other; users get the precision of filters where they know what they want, and the flexibility of semantic search where they don't.
Representative outcomes
Search that understands intent
Relevant results even when query wording doesn't match content exactly.
Fewer zero-result searches
Semantic matching surfaces relevant content that keyword search would miss.
Faster discovery in large catalogs
Effective search over content sets too large or varied for manual filtering alone.
Delivered through
Related work
Relevant industries
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