Building an LLM Gateway for Your Startup

A technical deep-dive into building a self-hosted LLM proxy layer that sits between your mobile/web clients and model providers — covering model routing and automatic fallback chains (Claude → GPT → local Llama), semantic caching using embedding similarity search with pgvector to serve duplicate-intent queries from cache, per-user token budget enforcement with sliding window rate limiting, streaming response passthrough with backpressure handling, and the Ktor/FastAPI implementation patterns that let a single VPS handle thousands of concurrent AI requests while cutting your LLM API bill by 70%+