The end-to-end platform for vector embeddings

Launch impactful vector-based workflows, from data to dashboard within your python notebook.

  • Analyze unstructured data using deep learning vectors
  • Rapidly experiment and evaluate different vectors
  • Interactive frontend apps to embed, share insights and drilldown

Experiment and deploy vector workflows at scale

Through rapid experimentation and prototyping, Relevance helps teams build out vector-based workflows such as clustering, zero-shot classification, vector search and more rapidly at scale. Helping data teams drive more impact quickly.

  • 100+ million

    Weekly API requests

  • 3 million

    End users

Effortlessly go from data to production

Deploy and experiment quickly

Extract, store, experiment and deploy vectors into a frontend dashboard. The end-to-end lifecycle all in a few lines of code.

  • Easy to use Python Library
  • Optimized for developer experience
  • Deploy into dashboard easily
Python Documentation

Extract vectors easily from your existing models

Integration with tools such as HuggingFace, SentenceTransformers, TensorFlow, PyTorch, OpenAI and more.

  • Bring vectors from your own model within a few lines of code
Build apps quickly

One platform to faciliate your workflow

Go end-to-end with the most flexible platform to utilize unstructured data with vectors.

Work with vectors
  • Integrations with popular libraries
  • Store vectors and metadata together
  • Query & store multiple vectors simultaneously
  • Deploy flexibly with different vector database backend
Vector workflows
  • Vector similarity search with brute-force or approximate nearest neighbors
  • Flexible clustering from KMeans to HDBScan
  • Embeddings projector
Combine with essential database features
  • Filters & facets
  • Real time aggregations
  • Keyword matching
  • Deploy and schedule workflows

“Relevance AI allowed us to quickly deliver production-quality AI analysis from social media text and images that our 10k+ customers love and have used over 3 million+ times.”

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Hugh Stephens

Founder, Sked Social – Top Social Marketing Platform

“Relevance AI has allowed our app developers to create unstructured data insights that our millions of gamers love. We have seen apps where gamers are up to 200% more engaged.”

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Jason Lee

Director of Business Development, Overwolf – #1 In-game creators platform

“Relevance AI’s capabilities to analyze unstructured data has helped us surface to our users their bad tendencies and provide actionable recommendations to them that have increased our engagement and session times by 200%.”

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Founder, Gaming website with 15 million+ monthly traffic

“Relevance AI has not only helped uncover the actionable insights from our unstructured data that helps save millions in repeated construction mistakes. Relevance also helped to further align the business with the data team to become more data-driven.”

Image of Hugh Stephens from Sked Social

GM of Data Science, Listed construction company

No third-party store

Seamless integration with metadata

JSON based hybrid store enables storing and querying of metadata and multiple vector embeddings simultaneously. Integratable with popular data warehouse such as Snowflake, MongoDB, Databricks and more.

  • No need to rebuild vector indices
  • Just insert your vectors and start running
  • Integrate with popular data warehouses
Learn about vector databases
Understand and compare 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.

  • Clustering visualizations
  • Embeddings projector
  • Compare different vectors
Book a demo

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.

Our team is here to help

Our team is ready to help walk you through exactly how you can use vectors to create value out of your unstructured data.

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