Semantic
From words to meaning.
Relevant results beyond
keywords.
Search
waterproofcushionedfootwearoutdoor
Match foundRelated images found
Retrieval without complexity.
No vector databases to manage. No indexing pipelines to build. No synchronization jobs to maintain. Flexible Vector Database keeps your knowledge ready for every model and agent.
See the retrieval flow.MeetFlexibleVectorDatabase.
Turn your knowledge into AI context.
Generate embeddings with any embedding model available on Compute. Flexible Vector Database stores, indexes, and serves them for semantic search, recommendations, and RAG.
Beyondsearch.
Connect content, context, and intelligence.
Go beyond vector storage. Flexible Vector Database includes a built-in retrieval engine for semantic search, recommendations, and RAG, while exposing the underlying vectors through an API for complete flexibility.
See ComputeVisual
From images to similarity.
Related content through visual understanding.
Upload an imagewaiting
cell structuretexturepattern
Match foundRelated tissue images found
MakeDiscoverySmarter.
Find relationships, not just matches.
Flexible Vector Database maps queries and content into the same semantic space, allowing applications to understand relationships between concepts, retrieve relevant information, and surface similar content beyond keyword matching.
Context-awarematches.
Turn every interaction into a better recommendation.
Flexible Vector Database combines embeddings, metadata, and contextual signals to understand relationships across your data, creating recommendation systems that surface the most relevant content, products, and information based on similarity, context, and relevance.
Runner
Browsing running gear
Recently viewed
3 product signals
Recommended similar product
Because they browsed running gear
Recommend runner shoes
Why this match works
Cushioning and stability match active performance needs.
Chic
Browsing chic styles
Recently viewed
3 product signals
Recommended similar product
Because they browsed chic styles
Recommend chic picks
Why this match works
Elegant styles matched by refined preferences.
What Flexible Vector Database includes
Compute-coupled embeddings
Run embeddings in Compute and consume the output directly in retrieval, keeping indexing and search connected.
Synonym-aware search
Search for shopper language, not only exact catalog labels, so discovery can follow intent beyond literal product names.
Image search
Support visual discovery when the product starts from a look rather than a keyword, with the same retrieval layer behind it.
Behavior recommendations
Use viewed-product signals to guide searches toward related items and make product suggestions more relevant.
Bulk indexing
Process large, non-urgent imports asynchronously and keep catalog data ready for retrieval when indexing completes.
Live updates
Index catalog changes asynchronously and expose status updates as each product update completes in the background.
