
TraceForge is an AI-powered incident investigation platform designed to help development and engineering teams investigate software incidents faster and more systematically. When an incident occurs, engineers often need to search through logs, repositories, documentation, historical incidents, and system information before they can understand what went wrong. TraceForge brings these investigation steps into a single workflow. The platform uses an orchestrator to coordinate six specialized AI agents. Each agent focuses on a different part of the investigation process, allowing TraceForge to collect and combine evidence instead of relying on a single AI response. A typical investigation starts with an incident being opened in the TraceForge dashboard. The user can trigger an investigation, after which the orchestrator coordinates the available agents. The system analyzes the incident context, gathers relevant evidence, investigates potential causes, and produces structured investigation results that can help engineers understand the incident and decide on the next steps. TraceForge provides a visual interface for incidents, repositories, investigations, knowledge, and system settings. The goal is to transform incident investigation from a manual, fragmented process into a structured AI-assisted workflow. The project was developed with IBM Bob and demonstrates how AI-assisted development can be used to build a complete full-stack application with an agent-based architecture. TraceForge is designed as a hackathon prototype and focuses on demonstrating the complete incident investigation workflow, agent orchestration, evidence-driven analysis, and an intuitive developer experience.
27 Sep 2026