Supabase Vector
The open source backend for AI applications
Supabase Vector is an AI toolkit to power any AI application. - Store vector embeddings at scale, alongside your users data. - Works with any language, stack, or programming environment. - Example projects to get you started. - Start for free on our cloud.
Reviews for Supabase Vector
Hear what real users highlight about this tool.
Supabase Vector draws praise for fast setup, strong DX, and smooth Postgres integration. Makers of Warestack highlight it as the most effortless choice after trials with Pinecone, MongoDB, and SingleStore, citing flexibility and a helpful learning curve. Makers of notclass report straightforward semantic search with pgvector. Makers of chatWise value handling auth, embeddings, and vectors in one stack. Users echo easy onboarding, scalable querying, and quick wins like image search with minimal Python, calling it a practical way to ship AI features quickly.
This AI-generated snapshot distills top reviewer sentiments.
Vector database for review/response pairs RAG
Using Supabase and SupabaseVector to handle stuff from authentication to embeddings and vectors for LLMs.
Supabase Vector makes it ridiculously easy to manage embeddings for AI projects. I love that it’s open source, so you get transparency and flexibility while handling the complexities of AI backend tasks seamlessly.
Love using supabase vector, all integrations featured on Supacrawler all use supabase's pgvector extension which works perfectly for my use-case.
We use Supabase’s vector store to manage embeddings and deliver fast, accurate AI responses for our chatbots.
Supabase Vector has been a game changer for embedding search + recommendations. Open source, scalable, and actually pleasant to work with.
I was able to get image search going with just a couple lines of python code using the vecs client! Awesome DX!