TReNDS Implements Agentic AI for Automated Root-Cause Analysis
Researchers at Georgia State University have developed an automated pipeline using Amazon Bedrock to identify production errors in under a minute.
Original source published: August 7, 2026
The TReNDS research center at Georgia State University has introduced an agentic AI pipeline designed to streamline the investigation of production errors. By utilizing Amazon Bedrock alongside the open-source Strands Agents SDK, the system automates the root-cause analysis process, which previously required manual intervention. According to the report, this transition has reduced the time needed to identify issues from a range of 15 to 30 minutes down to less than 60 seconds.
For those learning about AI, this development highlights the practical application of agentic workflows in technical operations. It demonstrates how integrating generative AI models with specialized software development kits can automate complex diagnostic tasks, offering a template for how practitioners might apply similar agent-based architectures to improve efficiency in their own technical environments.