Custom AI Solutions

Zero documentation, full migration: AI solves the COBOL problem

Hundreds of legacy COBOL applications needed migrating to Java with no reliable documentation and deeply implicated logic. iForAI deployed a generative-AI approach that maps real application behavior automatically, reducing migration time and cost without relying on rare COBOL talent.

Engineers reviewing code on a tablet during a legacy system migration discussion.

Challenge

Manual, line-by-line translation of hundreds of legacy COBOL applications was too slow, too risky, and nearly impossible to test reliably.

The existing approach created limitations:

No reliable documentation for most applications
Deeply entangled, decades-old business logic
Heavy dependence on a decreasing pool of COBOL specialists
Manual translation that couldn't scale to the size of the migration

As the migration scope grew, the traditional approach directly limited how fast and how safely the organization could move to a modern, cloud-native architecture.

Solution

Mapped each application's real behavior through massive automated testing
Auto-generated a fresh PRD from verified, observed behavior not outdated documentation
Rebuilt each application cloud-native from the regenerated requirements
Reduced dependence on third-party COBOL-translation vendors and poor internal expertise

This allowed the migration to proceed from verified, current behavior instead of incomplete legacy documentation.

Results

Migration time compressed by approximately 50% compared to traditional line-by-line translation
Reduced dependence on COBOL specialists by over 70%
Delivered a repeatable migration playbook reusable across hundreds of remaining applications
Cut estimated third-party vendor costs by roughly 40%

Implementation