AWS Boosts AI Code Modernization

AWS is expanding its AI-powered service for modernizing legacy code, introducing custom transformations for upgrading languages and migrating frameworks at scale.

AWS is marking the one-year anniversary of AWS Transform, its agentic AI service designed to modernize enterprise applications. Initially focused on .NET, Mainframe, and VMware workloads, the service helps companies update legacy systems at scale. A significant new enhancement, AWS Transform custom, now allows organizations to move beyond pre-built modernizations and create their own specific transformation rules. Using these custom definitions, development teams can automate complex tasks like upgrading programming language versions, migrating between software frameworks, and analyzing entire codebases for performance optimizations.

This introduction of custom transformations is a crucial development for businesses struggling with the high cost and complexity of maintaining older software. Manually refactoring legacy code is a slow, resource-intensive process that often hinders innovation. By offering a customizable, AI-powered tool, AWS aims to automate much of this heavy lifting. This enables developers and IT teams to accelerate their modernization initiatives, reduce technical debt, and adopt modern cloud-native architectures more efficiently. For CTOs and IT leaders, it provides a strategic path to de-risk and speed up digital transformation projects without a complete, and often prohibitive, system overhaul.

Automates the complex and costly process of modernizing legacy code, helping companies reduce technical debt and accelerate cloud migration without complete rewrites.

Reduces engineering costs and time spent on maintaining old systems, freeing up resources for innovation. It de-risks large-scale digital transformation projects by providing a structured, AI-assisted path to modern application architectures.