Cornerstone OnDemand cuts database diagnosis time by 78% with Amazon Bedrock
Cornerstone OnDemand, a workforce solutions provider with 140 million users, built Orion AI, a multi-agent system using Amazon Bedrock and Strands Agents to automate database operations. Before Orion AI, its Enterprise DataOps team spent up to 45 minutes per incident manually diagnosing issues across tools and logs. The new system reduced diagnosis time to 10 minutes, a 78% improvement, while…
Key points
- Cornerstone OnDemand’s Orion AI slashed database diagnosis time from 45 to 10 minutes, a 78% reduction
- System automates 10+ manual steps in database workflows and reduces alerts by 65% via deduplication
- Built with Amazon Bedrock and Strands Agents, deployed on AWS ECS in six months by a three-person team
Orion AI works by routing requests to domain-specific agents—each handling a narrow function like SQL diagnostics or blocking analysis—using keyword-based routing for speed and semantic search for ambiguous queries. The system bypasses conversational memory for live metrics to ensure accuracy. Deployed on Amazon ECS, Orion AI also includes guardrails for safety, observability via CloudWatch and X-Ray, and cost tracking. Cornerstone shares its design principles—domain-splitting agents, hybrid routing, and session-scoped memory—as reusable patterns for other operations teams.
How Cornerstone OnDemand cut database diagnosis by 78% with Amazon Bedrock
AWS Machine Learning Blog · 7 October 2026
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This text was published by AWS Machine Learning Blog and written by Derek Ziehl. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
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