Case Study: Humata Achieves 4X Cost Savings and Better Performance with Supabase

Humata Scales with Supabase Achieving 4X Cost Savings and Enhanced Performance

Humata, an AI platform that lets users chat with and analyze all their documents, needed scalable, reliable, and cost-effective infrastructure as its user base grew to millions. Initially using Pinecone for vector database workloads, the company found the setup complex and expensive, especially with latency-driven replica requirements, and needed a way to simplify operations without slowing product development. Supabase was the vendor involved, providing Postgres, Auth, Realtime, and Vector support.

By moving from Pinecone to Supabase’s pgVector on a single 16XL instance, Humata consolidated semantic search and business data into one database, simplified infrastructure, and improved feature velocity. Supabase helped deliver a 4X reduction in vector database costs, a 75% cut in database spend, and better scalability and developer speed, while also supporting real-time collaboration and compliance needs.

Humata