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Home»Cloud»Why The Future Of AI Lies In Vertical Platforms
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Why The Future Of AI Lies In Vertical Platforms

Don MabonaBy Don Mabona2025-07-08No Comments4 Mins Read
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Achal Singi
Achal Singi, Vice President at WestBridge Capital and a Globee Awards judge in AI
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Artificial Intelligence has moved from science fiction to boardroom strategy, and increasingly, to the invisible plumbing behind our most critical systems. While consumer-facing chatbots and foundation models make the headlines, the true long-term value of AI lies elsewhere: in vertical platforms engineered for industry context, precision at scale, and repeatable business outcomes. According to Achal Singi, Vice President at WestBridge Capital and a Globee Awards judge in AI, the future belongs to startups that don’t just deploy AI, they operationalize it.

“This isn’t about riding the next wave,” Singi explains. “It’s about building infrastructure, intelligent platforms that become the backbone of global business.”

The Quiet Power of Intelligent Infrastructure

In a market now saturated with general-purpose tools, a new class of vertical AI systems is emerging, purpose-built platforms that are deeply embedded into industry-specific workflows. These solutions aren’t always flashy, but they are indispensable. They manage sensitive hospital data, optimize complex supply chains, and coordinate distributed technical teams. In short, they do the hard work.

Take Turing, a portfolio company of WestBridge, which applies ML to optimize how companies hire, match, and manage remote engineering talent. They started training data for large language models which has become core AI infrastructure and are now training AI models for Fortune 500 companies across their respective industry verticals “We’re witnessing the creation of a new layer of infrastructure for knowledge work which will be essential for building intelligent vertical platforms,” says Singi. “It’s not just about finding high performance engineers, it’s about ensuring they have industry context to deliver industry focused solutions at scale” 

The same principle of intelligent orchestration applies in healthcare, where data fragmentation, regulatory complexity, and high-stakes decision-making demand more than off-the-shelf AI models. Innovaccer, one of WestBridge’s most successful investments, provides a health intelligence platform that ingests clinical and operational data and transforms it into real-time patient risk scoring, care coordination, and value based care enablement.

From Stakeholder Insight to Strategic Scale

Since joining WestBridge, Singi has been instrumental in driving the firm’s $100M+ follow-on investment in Turing, and $50M+ follow-on investment in Innovaccer, to help such companies scale to hundreds of millions in revenues.  But it wasn’t just capital that Singi brought to the table, it was conviction rooted in deep vertical expertise and drive to create intelligent infrastructure.

He personally led diligence across the product, speaking with physicians, reviewing regulatory feasibility, and modeling returns across payer, provider, and government segments. That research led to greenlighting new AI modules for automated risk adjustment, government healthcare analytics, and real-time care navigation, each a concrete step in making AI an operational layer within health systems.

Acquisitions That Strengthen the AI Stack

In parallel, Singi helped Innovaccer identify and integrate three high-impact acquisitions: Cured, PQS, and Humbi. These deals extended the platform into adjacent areas like pharmacy engagement, conversational agent copilots, and contract analytics, all areas where vertical AI can drive real cost savings and better outcomes.

The results speak for themselves. UCHealth saw a 79% increase in patient engagement. CHI Health saved $2.75M through better billing coordination. CommonSpirit Health replaced nine legacy systems with one cohesive infrastructure, improving care delivery for 1.9 million patients. These aren’t hypothetical use cases. They’re evidence of AI used not for automation’s sake, but for real outcomes at enterprise scale.

Vertical AI: The Next Decade’s Competitive Edge

As Singi emphasizes, AI’s real value doesn’t lie in the model, it lies in the loop. The best platforms create intelligent feedback systems that learn continuously, adapt automatically, and deliver better decisions with every cycle. This makes them not just useful, but essential infrastructure.

“A vertical platform doesn’t just plug into an industry, it redefines how that industry operates,” Singi explains. “That’s what we look for. Not just novelty, but systems that scale.”

This is where most AI investors get it wrong. Chasing generality can create noise; chasing vertical depth builds defensibility. Companies like Innovaccer and Turing succeed because they align technical innovation with real-world complexity, where stakes are high, margins are thin, and workflows cannot break.

From Infrastructure to Impact

As boardrooms move from AI infrastructure to AI agents and copilots, investors like Achal Singi are shaping a new playbook: one focused on depth, integration, and outcomes. Whether it’s predictive pharmacy copilots, conversational healthcare agents, or automated engineering pipelines, vertical AI is proving to be the infrastructure layer that modern enterprises didn’t know they needed, but now cannot live without.

Singi’s investments are a reflection of that future: one where AI is not a feature but a framework, not a demo but a durable system. And in this world, vertical wins.

AI Artificial intelligence Vertical Platforms
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Don Mabona

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