Observe your AI applications the same way you observe everything else.
Trace LLM API calls, monitor prompt and response content, measure token usage, and track latency and error rates for every GenAI application you run.
AI applications are black boxes without observability.
Your GenAI feature calls GPT-4 or Claude dozens of times per user session. You have no visibility into which prompts are failing, which calls are slow, which sessions are expensive, or why the AI response quality has degraded since the last deploy.
Everything LLM Monitoring captures.
Real signals collected by the Watchlog Agent — available in your dashboard within 60 seconds of enabling.
LLM trace — every call visible.
See the prompt, completion, token count, latency, and cost for every LLM call in your application.
What LLM Monitoring gives you.
How engineering teams use LLM Monitoring.
LLM Monitoring inside the Watchlog platform.
LLM Monitoring is built on the same tracing infrastructure as APM — LLM calls appear as spans in your distributed traces, and AI Analysis can correlate LLM errors with infrastructure incidents.
Start LLM Monitoring in under 2 minutes.
No YAML. No complex configuration. The Watchlog Agent handles discovery automatically.
Start monitoring with LLM Monitoring.
Full LLM call visibility — prompt, completion, tokens, latency, and cost per call.
Questions? Talk to us → [email protected]