<ul><li>Evaluating conversational AI systems powered by large language models (LLMs) presents a critical challenge in artificial intelligence.</li><li>Existing evaluation methods struggle to assess the capabilities of these systems in handling multi-turn dialogues, integrating domain-specific tools, and adhering to complex policy constraints.</li><li>To address these limitations, Plurai researchers have introduced IntellAgent, an open-source, multi-agent framework designed to automate the creation of diverse, policy-driven scenarios.</li><li>IntellAgent combines graph-based policy modeling, synthetic event generation, and interactive simulations to evaluate conversational AI agents holistically.</li></ul>

Plurai Introduces IntellAgent: An Open-Source Multi-Agent Framework to Evaluate Complex Conversational AI System

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