When Sophos’s GenAI Council faced the question of deploying AI into its data pipeline infrastructure, their answer was immediate: no customer or employee data leaves our perimeter. The policy was clear. The implementation wasn’t. Organizations are learning that agentic AI execution inside their own security perimeter isn’t optional for compliance-first work.
Running ETL at Sophos means moving HR records, customer data, and financial information across systems. When the cybersecurity company started migrating 800+ production pipelines off two legacy platforms, the engineering team needed to modernize fast. A major acquisition doubled the scope overnight. That modernization couldn’t move forward until they solved a governance problem: how do you use AI to accelerate data pipeline development without sending sensitive data to third-party endpoints?
The answer was architectural, not policy-based. Sophos adopted Maia, which runs as a Snowflake Native App. Because pipeline execution happens entirely inside the company’s own cloud environment, data never leaves Sophos’s boundary. Maia operates from within their perimeter, governed by their own access rules.
“Once the data lands in our environment, Maia is executing that within our Snowflake perimeter, and the data never has to leave until it’s ready to be consumed,” says Jason Mulvin, Director of Enterprise Data at Sophos. “That was a huge win for us.”
For security and compliance leaders watching agentic AI adoption, this pattern matters more than the productivity gains. Yes, pipeline delivery improved from 10–16 hours to 2–5 hours. But the bigger shift is structural. Sophos is now preparing to open data pipeline creation to business teams under governance review, and moving toward a future where reporting systems, AI applications, and autonomous agents all consume governed data under the same access controls.
That’s not about speed. That’s about control. As agentic AI moves into production environments, the compliance question isn’t whether AI can do a task. It’s whether every consumer of data (human, application, or agent) answers to the same governance rules.
Sophos proved that boundary matters more than the labor savings. For organizations building their AI governance architecture, that’s the lesson worth copying.
Learn how Sophos achieves governed data delivery at scale. Read the full case study
