Project

AgentOps

Objective

The rapid growth of autonomous and semi-autonomous AI agents has introduced new challenges in monitoring, debugging, and optimizing agent-based workflows. AgentOps is a proposed framework aimed at delivering observability, testing, and performance analytics for AI-driven agents across diverse applications. This project will develop and implement a system for real-time tracking, error analysis, and reproducibility of agent behaviors, with the goal of improving reliability, transparency, and operational efficiency. The proposed solution will integrate seamlessly into existing development pipelines, supporting both research experimentation and production deployment.

Outcome

Expected outcomes include improved agent performance monitoring, enhanced decision-making transparency, and a scalable foundation for future advancements in AI agentic systems.