Back to Case Studies
    COBOL Modernization•3 min read

    Modernizing Manufacturing Systems with AI

    2-3x Faster Acceleration

    Situation

    A manufacturing client relied on core applications built in COBOL — systems developed over 30–40 years. These applications powered supply chain, warehousing, job scheduling, bill of materials, and back-office functions, making them indispensable to daily operations.

    However, the age and complexity of these systems created mounting challenges:

    • High technical debt from decades of custom COBOL development.
    • Shrinking COBOL talent pool limiting maintainability.
    • Business limitations hindering supply chain responsiveness and job scheduling, making it difficult to compete for fast client needs.
    • Needed a different approach to preserve core business logic but extend functionality in order to deliver differentiated services versus competitors.

    Task

    The client's objectives were clear:

    • Extract business logic and functional rules from COBOL into a canonical model.
    • Modernize representative COBOL modules into .NET microservices with APIs, UI, and data layers.
    • Map and transform legacy data schemas into cloud-native database models.
    • Validate AI's impact on speed, cost, and business value before committing to a multi-million-dollar program.

    Actions — Codemorphology's MORPH Process in Action

    M

    Map

    Ingested representative COBOL modules (simple, medium, and complex) and extracted their business logic, data flows, and rules into a canonical representation.

    O

    Orchestrate

    Decomposed COBOL into modularized business functions, clarifying dependencies and providing clear modernization roadmaps.

    R

    Reconstruct

    Generated .NET-based microservices, including APIs, UI/UX layers, and workflow logic, from the canonical models.

    P

    Produce

    Provisioned a development cloud environment, deployed .NET services, APIs, SQL transformations, and AWS Lambda microservices, and scaffolded DevOps pipelines for scale.

    H

    Harvest

    Captured learnings from the AI sprint and channeled them directly into the client's modernization program, enabling their teams to scale the factory approach confidently across additional modules.

    Results

    • Working Modernization Prototype: Delivered running .NET/AWS microservices for representative COBOL modules.
    • 2–3x Faster Acceleration: Demonstrated AI can compress modernization timelines from years to months.
    • Industry Best Practices Embedded: The AI went beyond replication — it enhanced reporting and analytics capabilities, helping the client deliver differentiated services in supply chain and scheduling.
    • Strategic Insight: The prototype validated the business case for AI acceleration, helping the client gauge what's possible and prepare for a confident scale-up.

    Summary

    By applying its MORPH process and deploying AI Agents, Codemorphology.ai helped a manufacturing client transform COBOL-era systems into .NET microservices and, more importantly, extend analytics capabilities to create new business advantages. The engagement gave the client the confidence to see how fast AI can accelerate modernization and how it can be applied to not just replicate legacy, but to enhance and differentiate for the future.