What it does
Open-source LLM engineering platform for observability, traces, metrics, evals, prompt management, datasets, and playground workflows.
Why it belongs here
Turns token burn into something you can inspect: traces, costs, regressions, and evals instead of vibes and surprise invoices.
Best use case
Product and engineering teams that need prompt traces, cost attribution, eval datasets, and quality review around LLM features.
How to use it
Instrument model calls with workflow and user metadata, review expensive traces weekly, and connect eval results to prompt or routing changes.
Limits
Observability shows where spend goes, but teams still need decisions about budgets, model choice, and acceptance criteria.
Tags
tracesevalscosts
