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Microsoft Research describes a synthetic enterprise data platform, grounded in public sources like O*NET, job postings, and SEC filings, for evaluating Microsoft Copilot's outputs on realistic business workflows. The piece is high-level and promotional: it gives no metrics, benchmark results, or methodology details, so its claims about catching issues generic benchmarks miss are unverified. For AI readers, the useful idea is the evaluation approach itself: privacy-safe synthetic environments as a substitute for sensitive production data.
From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence

Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. To resolve this tension, we built Industry Evaluation Data Generation Platform: full-scale synthetic enterprise environments grounded in publicly available real-world data sources such as O*NET occupational data, online job postings, and SEC filings. The synthetic environments mimic real business workflows, helping Microsoft find issues that generic benchmarks would miss. Safety and privacy are built into the platform by design. Every environment is fully synthetic and automated content-safety checks keep the generated data free of harmful or personally identifiable material. Every day, millions of knowledge workers around the world rely on Microsoft Copilot to draft documents, summarize meetings, surface relevant information, and accelerate productivity. Behind the scenes, this is powered by a network of AI systems, and ensuring they work as intended requires a thoughtful approach to evaluation. At Microsoft, we know that…
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