Ultra-low latency semantic caching layer for OpenAI, Anthropic, Gemini, and open-source LLMs. Reduce API bills by 80% and accelerate responses to <30ms.
My co-founder and I built EchoCache, a semantic caching layer for LLM APIs (OpenAI, Anthropic, Gemini, or anything OpenAI-compatible).
The problem: repeated user queries that are worded differently but mean the same thing still cost a full API call each time. Exact-match caching doesn't catch this. EchoCache embeds incoming prompts, checks similarity against past queries, and returns a cached response on a match — otherwise it passes through to your LLM provider as normal.
It's a drop-in wrapper — point your app at EchoCache instead of directly at the provider, nothing else changes. Free tier for smaller traffic, paid plan for higher-volume use like production support agents.
Site: https://echocache.vercel.app/
Happy to answer questions about the matching approach, false-positive handling, or anything else.