Case Study: Berri AI boosts productivity with Supabase Vector

Berri AI boosts productivity by migrating from AWS RDS to Supabase Vector

Berri AI, an API platform for creating custom ChatGPT instances on company data, needed a better way to manage its vector database. The team initially used AWS RDS to gain more control and reduce latency, but they ran into slow development cycles, debugging challenges, connection pool complexity, rollback headaches, and limited accessibility for non-database team members.

Berri AI migrated to **Supabase**, specifically **Supabase Vector**, to simplify database management and improve flexibility. The move reduced database update code from 40–50 lines to just one line, improved update velocity, made debugging faster, and gave the team a simpler UI and no-code ways to add columns. As a result, **Supabase** helped Berri AI streamline operations, boost productivity, and adapt more quickly to changing requirements.

Berri AI

Krrish D.

Co-Founder & CEO