The Enterprise AI Revolution: How Horizontal Platforms Are Unlocking GenAI’s True Potential

The GenAI Enterprise Dilemma

Despite massive investments in generative AI, large enterprises are facing a sobering reality: most implementations fail to deliver measurable returns. A recent landmark MIT study revealed that 95% of GenAI pilot programs struggle to demonstrate tangible business value, raising questions about whether companies are investing in AI simply because everyone else is doing so.

The GenAI Enterprise Dilemma
The Horizontal Solution Emerges
Proving the Model: Rapid Adoption and Growth
The Funding Race Accelerates
A Crowded Competitive Landscape
The Path Forward for Enterprise AI

The fundamental challenge lies in data accessibility. “For all the success of GenAI in the consumer sector, very few enterprises have been able to make it work for them,” explains Ragy Thomas, newly appointed chairman and co-CEO of UnifyApps. “That’s because GenAI needs access to the enterprise’s data to deliver on its promise – and it isn’t currently getting that access.”

The Horizontal Solution Emerges

Enter a new category of AI infrastructure: horizontal platforms designed to bridge the data silos that plague large organizations. Unlike vertical AI tools that target specific functions, these platforms act as connective tissue across the entire enterprise ecosystem.

“What we’ve built is an enterprise operating system for AI,” says UnifyApps co-CEO Pavitar Singh. “It’s a horizontal platform, rather than yet another vertical tool with AI embedded within it.” This approach represents a fundamental shift from point solutions to comprehensive AI infrastructure that can access, quality-check, and distribute data across all organizational verticals.

Proving the Model: Rapid Adoption and Growth

The market response to this horizontal approach has been dramatic. UnifyApps, founded just in 2023, has already secured an impressive roster of blue-chip clients including Lowe’s, HDFC Bank, Deutsche Telekom, and Belcorp, along with government clients in Abu Dhabi and Dubai. The company projects revenue growth of 600%-900% this year alone.

This explosive growth reflects what Thomas describes as an inflection point comparable to the early internet era. “The next decade will belong to AI-native enterprises,” he argues. “Every piece of software, workflow and process will be reinvented with AI at the core.”

The Funding Race Accelerates

Investors are betting heavily on this vision. UnifyApps recently announced a $50 million Series B round led by WestBridge Capital with participation from ICONIQ and other investors. This brings the company‘s total funding to over $80 million in less than 18 months, following an $11 million seed round in May 2024 and a $20 million round last November.

“The name of the game is speed,” emphasizes Thomas. With demand currently exceeding supply, the company has rapidly expanded from 100 to 400 employees over the past year and expects to reach 500 by year-end.

A Crowded Competitive Landscape

UnifyApps isn’t operating in a vacuum. The market for enterprise AI integration platforms includes established players like Workato and Zapier, along with companies such as Airtable, Pipefy, and Newgen. Perhaps most notably, data analytics giant Palantir Technologies represents a significant competitor in this space., as comprehensive coverage

However, investors believe UnifyApps’ horizontal approach positions it uniquely. “While most organizations are still stuck in experimentation, UnifyApps helps them scale real AI across workflows – securely, with strong governance, and with measurable ROI,” says WestBridge partner Rishit Desai. “We believe this is the infrastructure layer for the next generation of enterprise software.”

The Path Forward for Enterprise AI

The success of horizontal AI platforms suggests a new roadmap for enterprises struggling with GenAI implementation. Rather than focusing on individual use cases, organizations may achieve better results by first establishing the underlying infrastructure that enables AI to access and leverage data across silos.

This approach addresses the core challenge identified in numerous industry reports: that AI’s value diminishes when confined to departmental boundaries. By creating what amounts to a central nervous system for enterprise AI, horizontal platforms could finally unlock the transformative potential that has so far remained elusive for most large organizations.

As the race to dominate this emerging category intensifies, one thing becomes clear: the future of enterprise AI may depend less on developing smarter algorithms and more on building better connections between the AI tools and the data they need to access.