This project introduces AgentGuard, a monitoring and routing system designed to improve reliability and cost-efficiency in Azure-based agent workflows. By analysing early trajectory signals—such as reasoning patterns and tool usage—within the first 10–30% of an agent’s execution, AgentGuard predicts task outcomes and dynamically halts or re-routes agents to prevent failures. Calibrated with ADeLe for demand-aware evaluation, the system aims to optimise the Reliability–Latency–Cost frontier across diverse benchmarks, including software engineering and cybersecurity tasks. Expected outcomes include integrated Azure routing capabilities, diagnostic insights into team composition, and practical strategies for building more predictable, trustworthy agentic AI.
People
Jiang Chen
Researcher
Universitat Politècnica de València
David Gomez-Anton
Research Collaborator
Universitat Politècnica de València
José Hernández-Orallo
Professor
Universitat Politècnica de València
Haotian Li
Researcher
Yael Moros Daval
PhD Student
Universitat Politècnica de València
Peter Romero
Professor
Universitat Politècnica de València
Daniel Romero-Alvarado
PhD Student
Universitat Politècnica de València
Beibei Shi
Principal Research PM
Xing Xie
Assistant Managing Director