Vectorize + Supabase: Simplifying Vector Search for Your RAG Applications
We’re excited to announce our new integration with Supabase Vector, bringing Vectorize’s retrieval-augmented generation (RAG) pipelines to one of the fastest-growing open-source developer platforms.
If you’re already using Supabase and want to power smarter search, structured extraction, or multimodal AI experiences — this integration is for you.
Why Supabase?
Supabase has earned its spot as a developer favorite: Postgres under the hood, a clean API, and now pgvector support — all in one place. We’ve heard from our users time and again: “Let us use tools we already love.”
Supabase gives developers a modern database with built-in vector capabilities. And Vectorize makes it easy to turn raw documents into high-quality indexes and AI-ready pipelines. Now, you can do both — together.
RAG Pipelines, Now Supabase-Native
- Seamless Data Flow: Connect pipelines that ingest, chunk, embed, and index into Supabase Vector
- Stay in the Supabase Workflow: Keep using the tools and APIs you know, just with more AI firepower
From Data to Vectors
Supabase simplifies the process of managing your embeddings and building RAG pipelines. With just a few steps, you can set up and deploy a pipeline using Supabase’s powerful PostgreSQL and vector capabilities.
Vectorize handles the heavy lifting — data ingestion, preprocessing, and vector embedding — while Supabase takes care of storage and search. As your data changes, your embeddings stay up to date with automatic pipeline runs and built-in change detection.
Get Started in Minutes
- ✅ Sign up for Vectorize — free tier available
- 🔗 Connect your Supabase instance
- 🧩 Create your first pipeline — and you’re live!