TokenSaver — Cut LLM costs 30-40% with intelligent context routing.

The Problem AI teams running high-volume LLM fleets are hemorrhaging money on redundant context, system prompts re-sent on every API call, and cache misses that break savings. A trading firm or code agent shop easily burns $50K-$100K/week on tokens that could be compressed or routed to cheaper models. Existing solutions are fragmented point tools that don't talk to each other. What We're Building TokenSaver is a lightweight proxy that sits between your application and LLM APIs (OpenAI, Anthropic, Gemini). It automatically deduplicates identical context across requests, compresses long prompts using semantic analysis, and routes small tasks to cheaper models (Haiku for linting, Sonnet for generation). You swap one API endpoint, we handle the rest—no code changes needed. Who It's For Engineering leads and DevOps at mid-to-large trading firms, autonomous agent startups, and AI code generation platforms spending $50K+/month on LLM tokens. Key Features (Planned) Semantic context deduplicati