Agentic AI Modernization Platform
LiveBy Sammie Qadri · Updated
An AI-driven system that modernizes legacy mainframe applications through autonomous agent orchestration. Agents handle code documentation, code conversion, and workflow decision-making. The goal is migrating those applications to a modern, widely adopted backend language.
At a glance
- Modernizes legacy mainframe applications with autonomous agent orchestration
- Agents handle code documentation, code conversion, and workflow decisions
- Migration target: a modern, widely adopted backend language
- Integration patterns established for AI-enabled SDLC pipelines
- CodeScan: discovery tooling I helped establish and continue to support
Architecture
Autonomous agents handle documentation, conversion, and workflow decisions
Agentic AI workflows were architected to automate documentation, code conversion, and orchestration of legacy systems. The same autonomous agent orchestration covers workflow decision-making.
Integration patterns connect agentic work to AI-enabled SDLC pipelines
Integration patterns for AI-enabled SDLC pipelines were established as part of the same work, tying the agentic capabilities into the software development lifecycle.
Manual effort reduced, with modernization made scalable and repeatable
The work reduced manual effort and enabled scalable, repeatable modernization of legacy applications.
Discovery tooling: CodeScan
I helped establish CodeScan, an AI-powered modernization-discovery accelerator, and continue to support it. It analyzes legacy repositories to generate application specs, map dependencies and architecture, flag deprecated technology, and produce modernization recommendations with visual reports. It was demoed at an internal Innovation Day.