LLM routers can optimize for different factors like price, latency, quality, etc. Enterprises tend to have prepaid AI credits, minimum-spend agreements, cloud commitments, or commercial ceilings across OpenAI, Anthropic, AWS, Azure, and other providers. We’ll call these “AI commits”.

This project is designed to consider the state of an enterprises’ current AI commits and use it to inform LLM routing decisions alongside other common variables (price, performance, etc.). This is an early PoC built using LiteLLM.

Target audience would CFOs, Strategic Finance, FinOps, Cloud Finance, and AI Platform folks who care about making sure AI commit minimums are met, and maximums are not exceeded.

Would love any feedback from folks!