# Hindsight Sets a New Standard: #1 on the BEAM Benchmark

We’re excited to announce our new integration with **Supabase Vector**, bringing Vectorize’s [retrieval-augmented generation (RAG)](https://blog.vectorize.io/what-is-retrieval-augmented-generation/) 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](https://platform.vectorize.io/) — free tier available
- 🔗 Connect your Supabase instance
- 🧩 Create your first pipeline — and you’re live!

[Free RAG Pipeline Builder Free for developers. Affordable for enterprises.\
Get Started Now](https://platform.vectorize.io/)