TruLens

TruLens turns your LLM application into a transparent pipeline where you can see exactly what happens at each step. Instead of treating your AI as a black box, it captures inputs, intermediate steps, and outputs as structured traces.

The real power comes from feedback functions. You can attach quantitative evaluators that score things like relevance, groundedness, or factual accuracy. This means you get actual numbers on how well your RAG pipeline or chatbot is performing, not just gut feelings.

Debugging LLM apps is usually a nightmare. Your model gives a weird answer and you have no idea which part of your retrieval or reasoning chain broke. TruLens gives you the visibility to actually fix problems instead of guessing.

It works with OpenAI models out of the box and integrates with popular frameworks.

Why we use it: We’re evaluating it for our content pipeline. Knowing why a bot generated a bad article matters more than knowing that it did.

Verdict: If you’re building anything beyond a simple demo, proper observability isn’t optional anymore.