ChatGPT but for your dataThe possibilities are endless: Build customer service bots, chat with your developer documentation, and get easy answers to questions over 100+ page documents.
Retrieval Augmented GenerationUse Retrieval Augmented Generation (RAG) to supplement foundation models with your own data. Augment base large language models like GPT4 from OpenAI, LLaMa, Falcon, Claude from Anthropic, and more.
Long term memoryCreate AI agents using PostgreSQL as vector storage for AutoGPT. Leverage popular development frameworks like Langchain and LlamaIndex.
No need to learn a new database or query languagepgvector extends PostgreSQL to handle vector similarity search and storage of embeddings needed for LLM AI applications with reliability and ease.
All the tools you need for vector similarity searchExact and approximate nearest neighbor search, L2 distance, inner product, and cosine distance, and out-of-the-box support for up to 2000-dimensional vectors.
Timescale is cloud PostgreSQL++Run pgvector on Timescale’s fully-managed PostgreSQL cloud platform for an easy, cost-effective experience.
Developer conveniencesOne-click database forking for testing new models and different embeddings. Read replicas to scale query load. Free consultative support to guide you as you grow.
Secure and privateSOC2 Type II and GDPR compliance. Data encryption at rest and in motion. VPC peering for your Amazon VPC.
Transparent pricingNo “pay per query” or “pay per index”. Decoupled compute and storage for flexible scaling as your needs change.
No credit card required • Free for 30 days