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View Full Features →It tracks AI and LLM observability signals such as agent runs, LLM calls, error rates, token usage, tool executions, traffic patterns, duration, and trace context when the application is instrumented.
No. Sentry presents it as observability for agents, LLMs, vector stores, tools, and custom application logic, with emphasis on production debugging across the whole AI workflow.
The public AI observability page shows setup examples for Python OpenAI Agents through OpenAIAgentsIntegration and JavaScript Vercel AI SDK instrumentation.
Sentry describes prompt and response context as part of deep trace analysis, but teams should confirm SDK behavior, defaults, and privacy configuration before collecting prompt or response content.
No. Sentry AI Monitoring refers to AI and LLM observability for production behavior. Seer is Sentry's AI debugging agent for root cause analysis, fix generation, and related debugging assistance.
AI builders and operators use Sentry AI Monitoring to streamline their workflow.
Try Sentry AI Monitoring Now →Open-source LLM engineering platform that captures traces, runs evaluations, and helps teams analyze cost, latency, and quality across production AI apps.
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