Thomson Reuters, a global technology and AI provider for the legal, tax, and compliance industries, was running a number of older .NET Framework applications behind the scenes. These apps were still functional, but they were: - Expensive to maintain - Time-consuming to update - Slowing down delivery of new features and products As Matt Dimich, VP of Platform Engineering Enablement at Thomson Reuters, explained, the team was spending too much time manually upgrading old code. That work was competing directly with their product roadmap and limiting how quickly they could move on new ideas. Existing tools from other cloud providers helped in some areas, but they weren’t designed to modernize at scale or to fully leverage generative AI. Thomson Reuters wasn’t looking for a small, incremental improvement—they needed a way to **rethink how they modernize .NET at scale**, reduce technical debt, and free engineering teams to focus on higher-value innovation rather than repetitive upgrade work.

AWS Transform is described as the **first agentic AI experience for modernizing .NET applications at scale**. Thomson Reuters adopted it as a purpose-built tool to refactor and modernize large legacy .NET systems using AI-powered agents. These agents help automate complex tasks across the full modernization lifecycle, including: - Asset discovery - Codebase analysis - Modernization planning - Code refactoring - Execution and validation Thomson Reuters used AWS Transform to: - Modernize **1.5 million lines of code every month**, achieving a **4x boost in modernization velocity**. - Move applications from **Windows to Linux**, improving performance and reducing infrastructure costs. - Shift from .NET Framework to **cross-platform .NET**, cutting technical debt by **50%**. Teams could run **multiple jobs in parallel** via both a web interface and integrated development environments (IDEs). Long-running jobs were supported with re-authentication checkpoints, and the agentic capabilities adapted in real time as the work progressed. According to Dimich, AWS Transform felt like an extension of their engineering team—constantly learning, optimizing, and helping them move faster, rather than just acting as a static migration tool.

By using AWS Transform to modernize its .NET applications, Thomson Reuters achieved several measurable outcomes:

• 4x faster modernization
  They were able to modernize about 1.5 million lines of code per month, representing a fourfold increase in transformation speed compared to prior approaches.
• 30% lower costs
  By moving workloads from Windows to Linux, Thomson Reuters realized approximately 30% cost savings while also improving performance.
• Shorter transformation cycles
  Application transformation timelines dropped from months to just a single two-week sprint in many cases, which helped reduce disruption and accelerate delivery.
• 50% reduction in technical debt
  Migrating from .NET Framework to cross-platform .NET cut technical debt by about 50%, making the codebase easier to maintain and evolve.
• Improved security posture
  AWS Transform also helped uncover and fix security vulnerabilities tied to unsupported language versions and platforms, reducing risk as part of the modernization process.

Overall, this wasn’t just a code upgrade exercise. For Thomson Reuters, using AWS Transform helped **remove friction from engineering workflows**, enabling teams to focus more on building new, professional-grade AI and cross-platform solutions, while still maintaining the reliability expected from a long-established technology provider.