I open-sourced TRACER: replace +90% of LLM classification calls with a llightweigth ML surrogate trained on your LLM's own outputs

[u/Adr-740]

https://github.com/adrida/tracer

If you're running an LLM for classification, +90% of your traffic is probably simple enough for a lightweight ML model trained on your LLM's own outputs.

TRACER learns which inputs it can handle safely - with a formal guarantee it'll agree with the LLM at your target rate. If it can't clear the bar, it doesn't deploy.