Compress By Light Reach – Reducing LLM costs with prompt compression and model routing

Summary: Compress By Light Reach lowers large language model (LLM) expenses by combining lossless prompt compression with intelligent routing to the most cost-effective model that meets quality targets. It operates via an OpenAI-compatible API and provides teams with insights into savings, budgets, and usage.

What it does

It compresses repeated prompt context and selects the cheapest suitable model using quality controls, optimizing LLM request costs through an OpenAI-compatible API.

Who it's for

Teams and organizations seeking to manage and reduce AI costs across features and usage.

Why it matters

It addresses high LLM spending by making usage more visible, controllable, and efficient through compression and model selection.