How TReNDS automates root-cause analysis with Amazon Bedrock
60 seconds. That's how long it now takes TReNDS to root-cause production errors — down from 15-30 minutes of manual work — using agentic AI on Bedrock.
Why it matters
Real agent deployment doing multi-step autonomous work at scale. Shows how enterprises are moving agents from pilots to production workflows that measurably compress time-to-insight on critical operational tasks.
The key facts
10 to knowTReNDS (Georgia State University research center) deployed agentic pipeline on Amazon Bedrock
Reduced root-cause analysis from 15-30 minutes manual → <60 seconds automated
Built on Bedrock + open-source Strands Agents SDK
Real-time production error investigation use case
Multi-step autonomous workflow (agent behavior, not just a feature)
TReNDS (Georgia State University research center) deployed agentic AI pipeline on Amazon Bedrock
Uses open-source Strands Agents SDK
Automates root-cause analysis in production environments
Performance: 15-30 minutes of manual investigation → under 60 seconds
Real-time error investigation capability
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: TReNDS, a research center at Georgia State University, built an agentic AI pipeline on Amazon Bedrock and the open-source Strands Agents SDK that automatically investigates production errors in real time, reducing root-cause analysis from 15 to 30 minutes of manual work to under 60 seconds.