Search Intelligence
Every query understood, expanded, and rescued in under 50ms. Semantic search intelligence across the full pipeline, invisible to the user.
Five specialist models bring semantic understanding to every stage of the search pipeline: expansion, rescue, re-ranking, intent classification, and query decomposition. All share a single fine-tuned base, deployed on a fraction of a GPU. At 10M queries per day, the entire pipeline costs what a single cloud API endpoint would.
5 specialist models
How It Works
One specialist model per search stage,
all sharing a single fine-tuned base
Vague Queries Become Rich Semantic Terms
'Cozy blanket' should match 'fleece throw' but keyword search cannot make that connection. A specialist LFM expands vague queries into 10+ semantic terms at 45ms, invisible in autocomplete. Cloud LLMs expand well but at 200-500ms, visible to the user. The difference is whether expansion is a feature or a bottleneck.
Zero Results Rescued Before the Empty Page Renders
10-15% of e-commerce searches return zero results, each one a lost conversion. No search platform has a built-in rescue mechanism. A specialist LFM detects zero-result conditions and generates alternative queries via broadening, synonyms, and constraint relaxation before the empty page renders. Every rescued search is recovered revenue.
The Right Product in Position One
Your search returns relevant products in the wrong order. Position 1 has 20%+ higher CTR than position 3. BM25 ranking does not understand that 'gift for a coffee lover' means pour-over sets outrank mugs. A specialist LFM re-ranks 50 results in 45ms with no separate embedding infrastructure.
Complex Queries Decomposed for AI Shopping Agents
'Cheap waterproof running shoes for wide feet in blue.' Passing the full string to search produces poor results. A specialist LFM decomposes it into structured sub-queries: price constraint, feature, fit, activity, and color. Each sub-query routes to the optimal retrieval path. 45ms total.
Try each model
All Demos
Query Expansion
Transform vague queries into rich semantic search terms in under 50ms
'cozy blanket' → 10+ semantic terms in 45ms. Search autocomplete that cloud LLMs can't serve
Zero-Result Rescue
Recover failed searches with intelligent rewrites before the user sees an empty page
10-15% of searches return zero results, each one a lost conversion rescued in under 50ms
Semantic Re-Ranking
Re-order search results by semantic relevance. Put the right product in position 1
Re-rank 50 results in 45ms. Your search returns relevant products, just in the wrong order
Search Intent Classification
Classify query intent and disambiguate ambiguous searches in real-time
Does your search know what the user means? Classify intent + disambiguate in under 45ms
Query Decomposition
Break complex multi-intent queries into structured sub-queries for AI shopping agents
AI shopping agents can't handle 'cheap waterproof shoes for wide feet in blue.' Decompose it in 45ms
Ready to deploy in your environment?