Evaluating and Improving AI Agents at Scale with Microsoft Foundry

As AI systems evolve, the focus for enterprises has shifted from mere development to ensuring trust and responsibility in AI outputs. This necessitates a new integrated lifecycle that combines observability, evaluation, and experimentation, moving beyond traditional separate phases of model testing and deployment monitoring. Microsoft Foundry and Arize AX collaborate to provide a robust framework that supports continuous AI quality improvement through an ecosystem of flexible evaluation and observability tools. Microsoft Foundry offers enterprise-grade evaluation capabilities and agent development support, while Arize AX enhances observability and experimentation, allowing organizations to adapt new evaluators and models seamlessly. Together, they enable a feedback loop where data from model interactions is used to drive improvements, ensuring AI systems remain safe, fair, and compliant. This integration facilitates responsible AI at scale, providing automated monitoring, transparent governance, and continuous learning, with tools like Azure's content safety evaluators exemplifying how trace data, dataset benchmarking, and dashboard insights all contribute to a principled AI lifecycle.

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