Our experienced leadership team combines deep enterprise expertise with a proprietary AI platform to help organizations move their technology initiatives from concept to implementation.
Old Country AI today announced the relaunch of its enterprise c-platform, built to help organizations move beyond AI experimentation to real-world production deployments. Led by a team with deep experience across the enterprise technology, financial, legal, and regulatory industries, the company is poised 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 companies to scope projects, develop systems, test solutions, deploy production infrastructure, and generate knowledge base documentation within a single integrated environment. The result is a system designed to help organizations move from idea to production system faster and with more confidence.
Despite unprecedented global investment in artificial intelligence, most companies’ efforts fail to deliver real business results. A study cited by MIT researchers found that 95% of enterprise generative AI pilots fail to achieve measurable financial results, primarily because they are not fully integrated into operational workflows. Additional industry analysis by RAND estimates that more than 80% of AI projects fail, roughly twice the failure rate of traditional IT initiatives. Gartner also warns that up to 80% of AI initiatives fail to deliver the 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” across enterprise AI deployments.
Dan Gurman, Founder and CEO of Old Country AI. “Artificial intelligence is powerful when combined with real-world operational experience.” “Our team has spent years building and deploying enterprise systems in regulated industries. We combined that experience with the latest AI capabilities to design Old Country AI, which enables companies to move from idea to deployed system quickly, securely, and efficiently.”
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A platform designed for real-world enterprise AI
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 entire enterprise technology development lifecycle, including:
AI-powered project scoping and architecture
Tools that help organizations define and design technology initiatives faster and more clearly.
Workflow-native AI architecture
A system designed to work directly within an enterprise’s business processes, rather than as an isolated application.
Domain-specific intelligence
Models tailored to specialized enterprise tasks and industry-specific use cases.
Enterprise governance framework
Built-in controls designed for organizations operating in regulated environments.
Enterprise-grade infrastructure and deployment tools
Features that help organizations move their AI systems from prototype to trusted production environment.
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:
Founder and CEO Dan Gurman is an engineer and attorney who previously served as head of AI patents and business solutions at Adeia (NASDAQ: ADEA), where he led artificial intelligence efforts focused on intellectual property and advanced technology systems.
Mike Olson, Chief Product Officer – Previously, Mike Olson was a Managing Director at UBS (NYSE: UBS), where he led product strategy and artificial intelligence efforts in complex financial and corporate environments.
Tara Thomas, Chief Business Officer — A longtime Silicon Valley product marketer who 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 includes leaders in technology, media, law, and artificial intelligence.
“Organizations implementing AI in regulated areas face particular challenges,” says Nigel Howard, advisor at Old Country AI and partner at Covington & Burling. “AI systems must adhere to compliance and governance frameworks that institutions rely on. Old Country AI understands this challenge and is approaching it with the appropriate seriousness that enterprise adoption requires.”
“Artificial intelligence is entering a stage where execution is more important than experimentation,” said Randall Rosenberg, advisor to Old Country AI and former CEO of the Interactive Advertising Bureau (IAB). “What stands out about Old Country AI is our focus on operationalizing AI within real-world businesses. Successful companies will be those that deeply integrate AI into their workflows.”
This advisory board is further strengthened by Genio CEO Stephen Gribben. He brings additional expertise in enterprise AI applications and innovation strategy, along with years of experience serving as an executive coach to CEOs of global Fortune 100 companies.
said Stephen Gribben, CEO of Genio. “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.” “What he and his team are building at Old Country AI addresses a problem many organizations face today: how to actually complete an AI initiative and make it work within the systems that run large enterprises. This is no easy task and requires both technical depth and operational insight.”
Transitioning from AI experiments to AI infrastructure
Over the past decade, organizations have run thousands of AI pilots across a variety of departments, from marketing to compliance. But many of those efforts never go beyond proof of concept.
“Years ago, I had a clear vision that AI could fundamentally transform enterprise workflows, but the technology wasn’t ready,” Garman continued. “Today, advances in AI, infrastructure, and automation are finally catching up to that vision. We can now deliver the kind of end-to-end transformation that large enterprises have been waiting for.”
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