Your AI agent completed the conversation. No error. But it hallucinated a policy, skipped a step, or did the wrong thing. Traditional monitoring sees a 200 OK. Ledda catches what monitoring misses. Connect OpenTelemetry traces in 10 minutes. See every LLM call, tool use, and decision. Get alerts when completion rates drop or hallucinations spike. Readable by your whole team, not just engineers. OpenTelemetry native. Free: 50k units, no credit card.

Framer — Launch websites with enterprise needs at startup speeds.

Launch websites with enterprise needs at startup speeds.

Hey PH! I'm Marcelo, founder of Ledda. I built Ledda because I kept seeing the same pattern: teams ship an AI agent, it works great in demos, then weird things start happening in production. The agent skips steps. It makes up policies. It confidently does the wrong thing. And nobody knows until a customer complains. The problem? These aren't errors. Traditional monitoring sees a 200 OK. The agent "completed" the conversation. But the customer got a hallucinated answer or a half-done task. Ledda watches every conversation your AI agent has and catches the failures that don't look like failures. Your support team can search conversations without asking engineering. Your product team can see patterns without parsing logs. We're OpenTelemetry native — if you have tracing, you can connect in 10 minutes. No SDK lock-in, no code changes to your agent. Would love your feedback. What's the hardest part of running AI agents in production for you?

Framer — Launch websites with enterprise needs at startup speeds.

Launch websites with enterprise needs at startup speeds.

Ledda

See what your AI agents are actually doing in production

See what your AI agents are actually doing in production