Sentrial offers a solution for monitoring and fixing AI agent failures in real-time. It allows users to not only observe issues but also automatically resolve them through code integration. The platform captures every interaction, including all LLM calls and tool uses, providing full visibility into agent performance. With features like complete execution traces, latency metrics, and input/output inspection, users can track performance in real-time. The service includes AI-powered root cause analysis to detect issues before they affect users, providing actionable fix suggestions and auto-detecting failures. Users can implement fixes directly into their codebase, benefiting from AI-assisted prompt editing and direct GitHub integration for seamless deployment. The platform enables hot-reload of changes without needing redeployment, which streamlines the process of addressing issues. Sentrial's monitoring capabilities extend to automated signal detection and sentiment analysis, helping identify patterns in agent performance. Users can analyze session data to understand failure patterns and improve overall functionality. The setup is easy; simply wrapping the LLM client captures all relevant data without extensive configuration. The pricing model is transparent, with clear access to documentation and support.