Tokonomy is a privacy-first token optimization proxy that automatically reduces LLM costs without changing your workflow. Unlike observability tools like gateways that only track usage, Tokonomy actively rewrites prompts to cut token waste. Unlike compression libraries that require SDKs, Tokonomy works instantly via proxy — and never stores prompts or responses.
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Maker
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We built Tokonomy after realizing how quickly AI costs were creeping up. Not because models were expensive, but because we were sending far more tokens than necessary. Between long system prompts, repeated context, and verbose tooling, it felt like we were quietly bleeding money on every request.
The problem is that most tools today help you measure AI usage, but very few help you reduce it. And the ones that do often require SDKs, complex setup, or sacrificing privacy.
Tokonomy started as a simple experiment: could a proxy intelligently compress prompts before they hit the model? Early versions focused on basic trimming, but that quickly evolved into LLM-powered rewriting, cache alignment, and smarter optimization, all while keeping the architecture stateless and privacy-first.
The goal became clear: build the FinOps layer for AI. Something that quietly sits in the middle, reduces waste automatically, and lets developers keep using the tools they already love.
We included an SDK too if that's your bag.