Inside the Transformation: How Thomson Reuters Is Becoming a Tech Company from the Inside Out

denise.lam@thomsonreuters.com — Tue, 02 Sep 2025 10:00:26 +0000

At ��, we’ve made a bold commitment: to become the world’s leading content-driven AI technology company. That transformation is most visible in the tools we deliver to customers, like CoCounsel, our agentic AI platform for legal, tax, compliance, and advisory professionals. But just as importantly, it’s happening internally in how we build, modernize, and scale the very infrastructure that powers everything we do.

Behind the scenes, we’re evolving our engineering culture, accelerating development cycles, and embedding AI into the way we work, because to deliver professional-grade technology externally, we must operate like a modern tech company internally.

Here’s what that transformation looks like in practice.

From Technical Debt to Engineering Velocity:

Every technology company navigates the balance between maintaining legacy systems and building for what’s next. For us, our .NET applications were a major bottleneck, slowing down innovation and tying up engineering time in maintenance instead of forward progress.

To tackle this, we partnered with AWS and joined the private preview of AWS Transform, an agentic AI-powered code modernization tool. The impact was immediate. What once took months of painstaking manual updates became a two-week sprint. Using agentic AI, we cut technical debt dramatically and lowered cloud operating costs by 30%.

But the bigger shift was cultural. Our engineers now spend less time managing legacy code and more time creating value. That’s what transformation looks like.

“This isn’t just a modernization story—it’s a mindset shift,” said Matt Wood, VP of AI Products at AWS. “�� showed what’s possible when you combine large-scale enterprise systems with next-generation AI tools. They didn’t just migrate—they accelerated how they build, think, and deliver.”

Cloud at Scale:

Innovation can’t thrive without a strong foundation. That’s why we undertook one of the most ambitious cloud migrations in our history: moving over 500 terabytes of data and 18,000 databases to Microsoft Azure SQL Managed Instance. This shift supported over 70,000 users across 7,000 firms and dramatically improved performance, scalability, and reliability. Working side by side with Microsoft’s engineering teams, we used automation, phased rollouts, and custom tooling to modernize without disruption. We eliminated legacy bottlenecks, streamlined backup and restore processes, and reduced infrastructure complexity across the board.

“Microsoft was invaluable, working closely with us to optimize load and troubleshoot at every stage,” said Bart Matzek, Senior Director of Technology, Solutions Engineering at ��. “This deep collaboration empowered us to build new technical capabilities and resilience. Our team emerged stronger—better equipped to deliver reliable, high-performance solutions to our customers.”

“We’re proud to support �� in this journey,” said Arpan Shah, General Manager of Azure Infrastructure at Microsoft. “Their scale, complexity, and ambition make them a model for how modern enterprises can evolve their platforms to unlock agility, reliability, and innovation through the cloud.”

This wasn’t just about lifting and shifting infrastructure. It laid the foundation for everything we’re building next: agentic AI systems, real-time decisioning, and seamless integration across domains.

AI Agents in Action:

We’re not just building agentic AI for customers. We’re embedding it into how we operate.

One powerful example is our AI Data Analyst Agent, built in partnership with the Snowflake AI Data Cloud. This system interprets natural language queries, performs operations, and surfaces real-time insights to non-technical teams across support, finance, and operations.

“Before this agent, analyzing support cases was a manual, monthly process,” said Rittika Jindal, Principal Engineer at ��. “Now it happens daily, automatically, and gives time back to teams to focus on the customer experience.”

We’ve built this using Snowflake’s unified platform and deployed it with governance, scalability, and reliability top of mind. Powered by LLMs like Anthropic’s Claude via Snowflake Cortex AI and observable with tools like TruLens and AgentBench, this system is secure by design. Our data never leaves Snowflake.

This is AI that works, not just in theory, but at scale and with trust.

The Bigger Picture: Operating Like a Technology Company

These aren’t isolated initiatives. They’re signals of a broader shift. Across ��, we’re applying the same mindset we bring to customer-facing products: agile, AI-powered, and engineering-led.

We’re modernizing our tech stack. We’re hiring and empowering top-tier engineering talent. And we’re building AI into everything from code migration to platform orchestration.

This is what becoming a technology company looks like, from the inside out.

Because for us, it’s not just about what we sell. It’s about how we think, how we build, and how we move.��

News Archives - Thomson Reuters Institute

Inside the Transformation: How Thomson Reuters Is Becoming a Tech Company from the Inside Out