Why We Built Vector Panda
In 2022, our founding team was building ML-powered applications at scale. We kept hitting the same problems: existing vector databases were complex, expensive, and unpredictable.
Configuration hell. Usage-based pricing that created billing anxiety. Approximate algorithms that missed critical results. We knew there had to be a better way.
So we built Vector Panda with three core principles: zero configuration, perfect recall, and transparent pricing.
Today, thousands of developers use Vector Panda to power semantic search, recommendations, and RAG applications. From startups to enterprises, we're proud to make vector search accessible to everyone.