Breezelearn
- Problem
- Model calls were slow and expensive, and every dashboard view leaned on the database to build context.
- What I did
- Built the Next.js platform for an AI customer-support product, and a Node.js orchestration layer connecting production APIs to Python ML services, with RAG workflows on vector databases and Redis.
- What happened
- 250K+ inference requests a day at under 400 ms. Primary database load down 61%.
- Next.js
- Node.js
- RAG
- ML serving