Recodez

The platform analyzes existing source code including COBOL, VB6, legacy Java, and older PHP or Python versions understands its business logic, and generates equivalent implementations in modern target languages with appropriate design patterns, testing scaffolding, and documentation.

This AI-augmented translation approach preserves the institutional knowledge embedded in legacy systems while delivering code that modern developers can understand, maintain, and extend.

The transformation pipeline is not a one-shot translation but an iterative, human-supervised process: Recodez generates candidate modern code, engineers review and refine it, and the feedback is incorporated to improve subsequent transformation quality across similar patterns in the rest of the codebase.

This collaborative approach is critical for production systems where subtle business logic edge cases, regulatory calculations, legacy data format handling must be preserved exactly, and where automated translation confidence must be verified by engineers who understand the domain.

The platform maintains a semantic diff view that highlights what changed between original and transformed code, making review efficient rather than requiring engineers to read both versions from scratch.

For financial institutions, government agencies, insurance companies, and other organizations running critical systems on decades-old technology, Recodez addresses one of the most pressing technology risk challenges of the modern era: the shrinking pool of developers who understand legacy languages, the growing cost of maintaining aging infrastructure, and the competitive disadvantage of being unable to iterate at modern software development velocity.

By dramatically reducing the cost and risk of modernization, Recodez opens the path for organizations that have previously deferred migration indefinitely to begin systematic, manageable modernization programs with predictable timelines and costs.