AgentOps Replay: A Trustworthy Framework for Multi-Agent Compliance Monitoring and Event Replay in Cognitive AI Systems

Abstract

AgentOps Replay is an open-source framework that enables deterministic event replay and automated compliance monitoring for multi-agent AI systems. It provides realtime observability, causal trace reconstruction, and fine-grained policy enforcement without compromising runtime efficiency. Unlike existing tools such as LangSmith or Arize Phoenix, our system integrates a low-overhead replay engine with a rule-based compliance layer that detects violations in cost, data privacy, and security access. Evaluation on 200 agent sessions across four agent types demonstrates a replay fidelity of 99.4 %, compliance detection accuracy of 94.2 %, and less than 3% performance overhead. A real-world deployment in an e-commerce environment further validates the framework's scalability and trustworthiness. By combining deterministic replay, automated auditability, and explainable flagging, AgentOps Replay advances the state of trustworthy AI monitoring for safety-critical applications.