Agents in action
Cornerstone's Orion AI cuts database diagnosis from 45 to 10 minutes
Cornerstone OnDemand's DataOps team built Orion AI, a multi-agent system on Amazon Bedrock and Strands Agents, to handle database incidents. A three-person team delivered it in six months.
45 → 10 minDatabase diagnosis time per incident, 78% faster
What the agent did
- Three specialized agents share each SQL Server investigation, replacing about 45 minutes of manual querying and log cross-referencing with about 10 minutes.
- Orion AI finds the root cause, recommends a fix and creates a populated Jira ticket assigned to the right on-call engineer, collapsing a four-step manual handoff into one interaction.
- Lifecycle tasks that took 10 or more manual steps now run as one natural-language interaction.
- Deduplication, threshold filtering and cross-signal correlation cut redundant alerts by a median of 65%, so 3–4 of every 10 former alerts reach engineers.
- The SRE-to-data-team reporting lag fell from 15 minutes to instantaneous.
Why it matters
The results come from narrow, domain-scoped agents, keyword-first routing and a bypass of memory for live metrics. Routine incident diagnosis and coordination is where this team saw the biggest time savings. Destructive operations stay behind a human confirmation gate.
The figures are Cornerstone's own, published on an AWS blog, and the 65% alert reduction is a median.
Source: AWS Machine Learning Blog
Every number on this page comes from the source. Our charts redraw those numbers; videos are embedded from the publisher.
Agents in this story
| # | Agent | Gid Score | Downloads 7d | 7d | 30d | Stars | Latest release | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 15 | 63 | 8.7M | down 0.4% | up 7.1% | 8,746+20/day | 0.2.0yesterday | |||||
| No agents match that filter. | |||||||||||
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