Noah Labs Brings Secure AI to Government Systems
Some of the software still powering government agencies, defense operations, and regulated industries was built decades ago. Many of these systems continue running on older programming languages like COBOL, Ada, and C++, creating a growing challenge for organizations trying to modernize while maintaining strict security standards.
For many agencies, replacing those systems entirely is not realistic. At the same time, most public AI tools cannot be used inside highly sensitive environments where data security and infrastructure control are critical.
Noah Labs is focused on solving that problem through its platform, Sentinel.
Led by Murat Işık, the company has developed Sentinel as an AI-powered software development environment built specifically for secure and regulated industries. Instead of relying on cloud-based AI systems, Sentinel operates inside the customer’s own infrastructure, allowing organizations to use AI without exposing sensitive code or internal systems to outside networks.
The platform is designed to help engineering teams understand aging codebases, modernize outdated software, improve documentation, and speed up development workflows that would otherwise take significantly longer using traditional processes.
Murat’s background includes research work tied to Stanford University, participation in StartX, and previous AI projects connected to the U.S. Air Force. That experience helped shape Noah Labs around a growing issue in enterprise AI: many of the industries that could benefit most from artificial intelligence are also the least able to use public AI infrastructure.
Sentinel reflects a broader shift happening across the AI industry as organizations move beyond consumer chatbots and begin looking for systems capable of operating inside real-world enterprise and government environments.
For Noah Labs, the goal is not simply faster coding. It is creating a secure path for governments and regulated industries to modernize critical systems while keeping full control over their infrastructure, security, and data.
Disclaimer:
This article is for informational purposes only and does not constitute official government, cybersecurity, or AI policy advice. Readers should verify all information through official sources before making decisions related to AI implementation or government systems.
