Go from Experiment to Production rapidly

In a few lines of code, deploy your vectors inside a scalable and flexible environment.

  • Deploy to an API in few lines of code
  • No dev-ops or backend expertise required
  • Integrate with existing databases

No credit card required

Experiment and deploy vectors at scale

Relevance AI helps teams quickly and confidently build out vector features and interpretable data applications through rapid prototyping and experimentation at scale. Helping business become more and more data driven.

  • 100+ million

    Weekly API requests

  • 3 million

    End users

Developer tools for vectors

Experiment and deploy quickly and effortlessly

Store, experiment, search and compare vectors. The end-to-end vector lifecycle all in a few lines of code.

  • Easy to use Python & JS Libraries
  • Optimized for developer experience
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Deploy with any vector database backend

Highly flexible vector platform that allows you to deploy into any nearest neighbour index or vector search database such as Elasticsearch, FAISS, Opensearch, Vespa, Vertex.AI and more. With integration and support for many popular data science tools such as Scikit Learn, TensorFlow, PyTorch, OpenAI and more.

Work with vectors
  • Vector & metadata hybrid store
  • Multivector queries and store
  • Vector groupbys
  • Integrations with many popular tools
Combine with traditional
  • Filters & facets
  • Aggregation
  • Keyword matching
  • Customisable scoring
Other Vector essentials
  • Clustering
  • Embeddings Projector
  • Experiments Comparator
  • Bias Tests
No third party store required

Seamless integration with metadata

Our JSON based hybrid store enables storing and querying of metadata and multiple vector embeddings simultaneously.

  • No need to rebuild vector indices
  • Just insert your vectors and start running
Learn about vector databases

Our team is here to help

If you have special deployment needs, such as your own vector database backend let us know.

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