Enterprises Shift Focus to Internal AI Engineering Capabilities

Regulated industries move away from off-the-shelf AI coding tools in favor of custom agentic systems

Published on Feb. 13, 2026

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A growing number of enterprises, particularly in regulated industries like financial services and automotive, are re-evaluating their reliance on generic AI coding tools and instead exploring the development of internally-built, domain-specific AI engineering platforms. These 'agentic coding systems' are designed to operate within existing governance, compliance, and domain structures rather than work around them.

Why it matters

As AI capabilities continue to evolve, organizations are seeking to balance experimentation with risk management, regulatory alignment, and strategic control of intellectual property. The shift toward agentic coding systems reflects a broader trend of enterprises prioritizing proprietary domain knowledge as a long-term competitive asset.

The details

Organizations operating in regulated sectors have encountered challenges with the use of generic AI systems in production environments due to security requirements, legal review processes, domain-specific constraints, and compliance obligations. Several companies have publicly discussed building internal AI-assisted engineering systems, such as Ramp's code review tool Ramp Inspect, to better align with industry standards and governance frameworks.

  • Over the past three years, organizations across industries have experimented with AI copilots and general-purpose coding assistants.
  • Industry analysts suggest that enterprises will increasingly differentiate between generic AI productivity tools and agentic coding systems in the coming years.

The players

Hexaview Technologies

An engineering services firm focused on AI-enabled systems and enterprise technology implementation, working with financial services and regulated-industry clients.

Ramp

A company that has developed an internal code review system known as Ramp Inspect.

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What they’re saying

“Enterprise agentic coding requires a different approach than general-purpose AI tools. Regulated organizations need systems that operate within their existing governance, compliance, and domain structures, not around them.”

— Ankit Agarwal, CTO at Hexaview Technologies

What’s next

Industry analysts suggest that enterprises will increasingly differentiate between generic AI productivity tools and agentic coding systems designed to operate within existing governance and compliance frameworks as AI capabilities continue to evolve.

The takeaway

The shift toward agentic coding systems reflects a broader trend of enterprises prioritizing proprietary domain knowledge and the need to balance AI experimentation with risk management, regulatory alignment, and strategic control of intellectual property.