What you can do
What you can do with Vespa Vector.
Index embedding vectors alongside structured data for hybrid search queries
Search by vector similarity to find semantically related documents and products
Update vector representations incrementally as ML models are retrained
Operations
Vespa Vector operations.
Search
Feed Document
Get Document
How it works
How it works.
- Add itDrop the integration onto the Workflow canvas or attach it to a Scheduler job — no code.
- ConfigurePick the operation and fill in the fields; credentials are stored encrypted and resolved only at run time.
- RunExecute it inline as part of an automation, or on a cron or interval at fleet scale.
Related
More Vector Database integrations.
Annoy
Build and query approximate nearest neighbor indexes using the Annoy library
Chroma
Store, query, and manage vector embeddings in ChromaDB collections
DocArray
Store, query, and manage document vectors and embeddings with DocArray
FAISS
Perform vector similarity searches and manage indexes using FAISS library
Haystack
Build document search and question-answering pipelines with Haystack
Jina AI
Generate embeddings and run vector search queries using Jina AI services
Wire Vespa Vector into your operation.
AccuOSS deploys AccuOps and builds the automations that put integrations like this to work.