Mohi is an advanced platform designed to enhance the performance and reliability of AI agents through comprehensive monitoring and optimization. By providing deep insights into agent behavior, real-time performance metrics, and AI-powered prompt tuning, Mohi ensures that AI agents operate efficiently and effectively at scale. Key Features and Functionality: - Comprehensive SDK: A framework-agnostic SDK that captures every execution detail from AI agents, including nested function calls, arguments, results, and hierarchical trace relationships, offering complete observability. - Hierarchical Trace Visualization: Interactive graphs that display parent-child relationships and execution flows, facilitating a clear understanding of agent operations. - Real-time Session Monitoring: Live monitoring of agent sessions with instant updates and insights, enabling prompt identification and resolution of issues. - Automatic Prompt Tuning: An AI-driven system that continuously analyzes agent performance patterns and automatically optimizes prompts and parameters to improve response quality and overall effectiveness. - Intelligent Quality Analysis: An AI-powered critique system that provides severity-based feedback and actionable insights to enhance agent performance. - Performance & Regression Detection: Tools to track agent performance over time with automated regression detection, ensuring consistent and reliable behavior. Primary Value and Problem Solved: Mohi addresses the challenges of monitoring and optimizing AI agents by offering a suite of tools that provide complete visibility into agent behavior, real-time analytics, and automated improvements. This comprehensive approach allows developers and organizations to build, test, and deploy AI agents with confidence, ensuring they perform reliably and effectively in various applications.