
The Problem Many organizations still depend on decades-old software that is critical to their operations. When new developers join these projects, understanding the system can take weeks or months because knowledge is distributed across legacy source code, configuration files, documentation, tickets, and Git history. Developers often struggle to answer basic but important questions such as: “What does this code do?”, “Why is this machine in an alarm state?”, “Which files are responsible for this behavior?”, and “What changed recently?” Our Solution ForgeBridge AI is an AI-powered legacy code intelligence and modernization assistant designed to make complex legacy systems easier to understand and connect with modern applications. Our prototype uses a legacy industrial manufacturing system, AUTOFACTORY-2005, as a real working example. The system analyzes legacy C/COBOL-oriented code, configuration, documentation, tests, tickets, and Git history to build contextual answers about system behavior. A developer can ask questions such as: “Why is Machine 7 in alarm state?” “What happens when the temperature exceeds the configured limit?” “Which files are responsible for this behavior?” “What changed recently in the legacy system?” ForgeBridge combines specialized analysis components for legacy code, system structure, Git history, and machine behavior. An orchestration layer coordinates these components and exposes the resulting intelligence through a modern FastAPI backend and web interface. For example, the legacy AUTOFACTORY-2005 system identifies Machine 7 as being in an alarm state because the configured temperature limit has been exceeded. ForgeBridge can connect this operational result back to the relevant legacy logic and configuration instead of requiring a developer to manually search through the codebase. Target Users The primary users are software developers, maintenance engineers, technical leads, and teams responsible for maintaining or modernizing legacy systems. What Makes It Unique ForgeBridge does more than generate explanations from source code. It combines code structure, configuration, operational behavior, tests, documentation, and version-control history into one contextual view. It also demonstrates a bridge between a legacy manufacturing system and a modern REST API, showing how legacy intelligence can be exposed to contemporary applications without modifying the original control logic. Impact By reducing the time required to understand unfamiliar legacy systems, ForgeBridge can support faster onboarding, troubleshooting, maintenance, and future modernization efforts while preserving valuable knowledge embedded in existing software.
27 Sep 2026