NEW YORK - TelAve -- Old Country AI (https://oldcountry.ai/) today announced the relaunch of its enterprise artificial intelligence platform (https://www.oldcountry.ai/platform), designed to help organizations move beyond AI experimentation and into full-scale production deployment.

As enterprise adoption of artificial intelligence accelerates, organizations are facing a critical challenge: most AI pilots never reach production. Old Country AI is built to close this gap by enabling end-to-end AI development (https://oldcountry.ai/about/), deployment, and operational integration within real business workflows.

Enterprise AI Is Failing to Deliver Production Outcomes

Despite unprecedented global investment in artificial intelligence, most enterprise initiatives fail to deliver measurable results.

Research cited by MIT, RAND, and Gartner shows:

• Up to 95% of enterprise generative AI pilots fail to deliver measurable financial results
• More than 80% of AI projects fail overall
• Many failures stem from lack of integration into operational workflows

Old Country AI was rebuilt specifically to solve this "pilot-to-production gap" across enterprise AI deployments.

"Artificial intelligence becomes powerful when it is paired with real operational experience," said Dan Gurman (https://oldcountry.ai/team/), 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."

A Unified Platform for Enterprise AI Development and Deployment

Old Country AI provides an integrated environment for enterprise AI development through its core platform (https://www.oldcountry.ai/platform) and enterprise AI services (https://www.oldcountry.ai/services), enabling organizations to:

• Scope and design AI initiatives
• Build and test AI-powered systems
• Deploy production-grade infrastructure
• Integrate AI into business workflows
• Generate supporting technical documentation

Core platform capabilities include:

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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.

Built for Regulated and Complex Enterprise Environments

Old Country AI focuses on environments where accuracy, governance, and operational integration are essential. Learn more about enterprise AI services (https://www.oldcountry.ai/services) supporting:

• Financial services
• Legal services
• Enterprise technology
• Digital media

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.

• Dan Gurman (https://www.oldcountry.ai) — Founder and CEO; former Head of AI Patent & Business Solutions at Adeia
• Mike Olsson (https://oldcountry.ai/team/) — Chief Product Officer; former Managing Director at UBS
• Tara Thomas (https://oldcountry.ai/team/) — Chief Business Officer; enterprise marketing and growth leader

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."

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"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.

"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."

From AI Experiments to Enterprise AI Infrastructure

Over the past decade, enterprise organizations have run thousands of AI pilots across departments. Many have not moved beyond proof-of-concept.

Old Country AI represents a shift toward enterprise AI infrastructure—systems that are operational, integrated, and embedded into core business workflows.

Explore the enterprise AI platform (https://www.oldcountry.ai/platform) and full services (https://www.oldcountry.ai/services) offerings.

"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."