Old Country AI Relaunches with Enterprise AI Platform Built to Close the “Last Mile” Between AI Pilots and Production

Experienced leadership team combines deep enterprise expertise with a proprietary AI platform to help organizations move technology initiatives from concept to deployment.

Old Country AI today announced the relaunch of its enterprise cplatform, built to help organizations move beyond AI experimentation and into real production deployment. Led by a team with deep experience across enterprise technology, finance, law, and regulated industries, the company is positioning itself to address one of the biggest challenges facing the AI industry today: turning promising AI pilots into operational systems that deliver measurable business value.

Old Country AI’s platform enables end-to-end AI-assisted development, allowing enterprises to scope projects, develop systems, test solutions, deploy production infrastructure, and generate supporting technical documentation within a single integrated environment. The result is a system designed to help organizations move faster and more confidently from idea to operational system.

Despite unprecedented global investment in artificial intelligence, most enterprise initiatives fail to deliver real business outcomes. A study cited by MIT researchers found that as many as 95% of enterprise generative AI pilots fail to deliver measurable financial results, largely because they never fully integrate into operational workflows. Additional industry analysis from RAND has estimated that more than 80% of AI projects fail, roughly twice the failure rate of traditional IT initiatives. Gartner has also warned that up to 80% of AI initiatives fail to deliver their intended value due to governance challenges, data issues, and difficulty integrating AI into enterprise operations.

Old Country AI was rebuilt specifically to solve this “pilot-to-production gap” that has emerged across enterprise AI deployments.

“Artificial intelligence becomes powerful when it is paired with real operational experience,” said Dan Gurman, Founder and CEO of Old Country AI. “Our team has spent years building and deploying enterprise systems in regulated industries. We designed Old Country AI to combine that experience with modern AI capabilities so companies can move from ideas to deployed systems quickly, safely, and efficiently.”

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Platform Designed for Enterprise AI in the Real World

Old Country AI focuses on environments where accuracy, governance, and operational integration are essential, including regulated sectors such as financial services, legal services, enterprise technology, and digital media. The company’s platform supports the full lifecycle of enterprise technology development, including:

AI-assisted project scoping and architecture

Tools that help organizations define and design technology initiatives with greater speed and clarity.

Workflow-native AI architecture

Systems designed to operate directly inside enterprise business processes rather than isolated applications.

Domain-specific intelligence

Models tailored to specialized enterprise tasks and industry-specific use cases.

Enterprise governance frameworks

Built-in controls designed for organizations operating in regulated environments.

Enterprise-grade infrastructure and deployment tools

Capabilities that help organizations move AI systems from prototype to reliable production deployment.

Automated documentation and knowledge capture

AI-driven tools that generate technical documentation and system knowledge throughout the development process.

Leadership With Deep Enterprise and Regulatory Experience

Old Country AI is led by a team with extensive experience across enterprise software, financial services, artificial intelligence, and legal frameworks.

The leadership team includes:

Dan Gurman, Founder and CEO — a technologist and attorney who previously served as Head of AI Patent & Business Solutions at Adeia, (NASDAQ: ADEA), where he led artificial intelligence initiatives focused on intellectual property and advanced technology systems.

Mike Olsson, Chief Product Officer — formerly a managing director at UBS (NYSE: UBS), where he led product strategy and artificial intelligence initiatives within complex financial and enterprise environments.

Tara Thomas, Chief Business Officer — a long-time Silicon Valley product marketer who has led enterprise marketing, growth strategy, and demand generation initiatives across multiple technology organizations.

Advisors With Experience Across Technology, Media, and Law

Old Country AI’s advisory board brings together leaders from technology, media, law, and artificial intelligence.

“Organizations deploying AI in regulated sectors face particular challenges” said Nigel Howard, advisor to Old Country AI and partner at Covington & Burling. “AI systems must adhere to compliance and governance frameworks that institutions trust. Old Country AI understands this challenge and is approaching it with the appropriate seriousness needed for enterprise deployment.”

“Artificial intelligence is entering a phase where execution matters more than experimentation,” said Randall Rothenberg, advisor to Old Country AI and former CEO of the Interactive Advertising Bureau (IAB). “What stands out about Old Country AI is its focus on making AI operational inside real businesses. The companies that succeed will be the ones that integrate AI deeply into their workflows.”

The advisory board is further strengthened by Stephen Gribben, CEO of Genio, who brings additional expertise in enterprise AI applications and innovation strategy, along with many years of experience serving as an executive coach to CEOs of Fortune 100 global companies.

“I’ve known Dan for years and have always been impressed by his instinctive understanding of the intersection between enterprise technology and real business transformation,” said Stephen Gribben, CEO of Genio. “What he and the team are building at Old Country AI addresses a problem many organizations face today: how to actually bring AI initiatives to completion and make them work inside the systems that run large enterprises. That is not an easy task and requires both technical depth and operational insight.”

A Shift from AI Experiments to AI Infrastructure

Over the past decade, enterprise organizations have run thousands of AI pilots across departments ranging from marketing to compliance. Yet many of those initiatives never move beyond proof-of-concept.

“Years ago I had a clear vision for how AI could fundamentally transform enterprise workflows, but the technology simply wasn’t ready,” continued Gurman. “Today, advances in AI, infrastructure, and automation have finally caught up to that vision. We can now deliver the kind of end-to-end transformation that large organizations have been waiting for.”

Also Read: ​​The Infrastructure War Behind the AI Boom

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