Every LLM app I've built has the same broken pattern. Request comes in - reconstruct context from...
A solo founder built StreamCtx, a streaming context database for LLM apps persisting session state in real-time. Replaces 3-5 separate tools (Redis, vector DB, middleware) with one layer, cutting operational complexity for teams scaling LLM applications.
Every LLM app I've built has the same broken pattern.
Request comes in - reconstruct context from scratch - call LLM - throw context away.
It's wasteful, slow and breaks at scale.
The Problem
Most developers building ai app end up stitching together Redis, vector database and custom middleware just to give their app basic memory.
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