The vector platform for rapid experimentation
Build great vector-based applications with flexible developer tools for storing, querying and experimenting with vectors.
- Rapid experimentations with vectors
- Flexible vector evaluation tools
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Experiment with vectors at scale
We work with teams to enable vector features and rapid prototyping at scale. All of our functionality is available via API, SDK or dashboard.
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100+ million
Weekly API requests
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1 terabyte
Stored data
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3 million
End users
Vectors power the world’s technology giants
Companies like Google, TikTok and Spotify use vectors to work with their unstructured data.
- Google vectorize text for search
- Tiktok vectorize video and audio for “For You”
- Spotify vectorize music and lyrics for “Discovery”
Developer tools for vectors
Experiment and deploy quickly and effortlessly
Store, experiment, search and compare vectors in only a few lines of code.
- Easy to use Python & JS SDKs
- Optimized for developer experience
Learn how industry leaders are using vectors
Vectors are the secret sauce behind some of the most powerful features we use every day. Learn about how the tech giants take advantage of vectors.
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Pinterest’s vector recommendation engine
An insider perspective to decision makers about the benefits of a vector-based recommendation system
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Powerful ecommerce search with Taobao
Through the lense of one of the most successful ecommerce companies in the world, we showcase vector search.
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Replacing Algolia with Relevance AI discovery
Learn how you can create a more powerful discovery engine with our API.
Dive deep into vector experimentation
Highly flexible vector search that does not compromise on the traditional parts. Easily combine filters and exact text search with nearest neighbour vector search to create hybrid search.
Work with vectors
- Multivector queries
- Chunk search
- Hybrid vector store
Combine with traditional
- Keyword matching
- Facets & filters
- Aggregation
Analyse data
- Clustering
- Embeddings Projector
- Evaluation tools
No third party store required
Seamless integration with metadata
Our JSON based hybrid store enables storing and querying of metadata and vector embeddings simultaneously.
- No need to rebuild vector indices
- Just insert your vectors and search
Project your embeddings
Visualize, interpret and evaluate your vector space
Share how your vectors represent the unstructured data, then identify and interpret any biases with interactive visualizations.
- Embeddings projector
- Evaluation tools
“Relevance AI allowed us to quickly experiment and deliver production-quality semantic search that our customers love.”
Hugh Stephens
Founder, Sked Social
“Relevance AI has allowed our app developers to experiment and unlock features that our millions of gamers love. We are seeing gamers being more engaged than ever.”
Jason Lee
Director of Business Development, Overwolf
Analyze your vectors
Vector features go beyond search
Vectors have many great use case beyond vector similarity search such as vector clustering for topic modelling, dimensionality reduction for interpretation.
- Clustering for topic modelling
- Dimensionality reduction
Our team is here to help
Our data science team is ready to help walk you through exactly how you can use vectors to create value out of your unstructured data.
Schedule Demo