Why Riafy’s Google Cloud Win Signals a Shift in Enterprise AI

Kochi: Riafy Technologies, a Kochi-based AI company, has been named a 2026 Google Cloud Partner of the Year in the Social Impact: Accessibility Innovation category. The award, presented at Google Cloud Next 2026 in Las Vegas, recognises partners delivering measurable impact through deployed systems rather than experimental use cases.

The recognition comes at a time when enterprise AI is undergoing a reality check.

Industry leaders, including the CEO of TCS, along with recent McKinsey analyses, have pointed to a widening gap between pilot projects and production deployment, with a large majority of AI initiatives failing to scale beyond experimentation.

The more relevant question, then, is not how many pilots are launched—but which systems make it to production, and why.

Riafy’s platform, R10, is built around that requirement.

All enterprise AI agents deployed by the company are powered by R10, its enterprise AI platform designed to execute real-world business actions across systems. Unlike conventional AI implementations focused on conversational responses, these agents are built to complete workflows—booking tickets, processing transactions, resolving customer requests, and enabling operational processes end-to-end.

This shift from interaction to execution is where value is increasingly being created.

In aviation, Riafy’s deployment with IndiGo illustrates this transition. Its AI agent enables end-to-end customer servicing, including bookings, check-ins, and ancillary purchases. More significantly, it functions as a direct revenue channel, allowing transactions to be completed within the conversational interface itself.

Similar deployments span sectors including banking, telecom, commerce, and automotive, with enterprises such as Unilever Lakmé, Asian Paints, MG Motor and Federal Bank deploying Riafy’s AI agents to support customer engagement and operational workflows.

According to the company, its R10-powered systems have processed over one trillion tokens in live environments, operating at sustained high-volume throughput. While token scale alone does not define value, it signals a transition: AI systems are no longer peripheral tools—they are becoming embedded in core business operations.

“The Google Cloud Partner Awards honour the strategic innovation and measurable value our partners bring to customers,” said Kevin Ichhpurani, President, Global Partner Ecosystem and Channels, Google Cloud. “We are proud to name Riafy Technologies a 2026 Google Cloud Partner Award winner, celebrating their role in driving customer success.”

“India doesn’t need more AI demos. It needs AI in production — in every language, for every Indian,” said John Mathew, CEO & Co-Founder, Riafy Technologies. “At Riafy, our R10 agents on Google Cloud process trillions of tokens across industries. This recognition reflects what matters — systems that work reliably in the real world.”

Riafy’s trajectory reflects a broader pattern emerging in the AI ecosystem. Companies that have operated at consumer scale are increasingly leveraging that experience to build enterprise systems capable of handling variability, scale, and real-world complexity.

Founded in 2013, Riafy spent over a decade building AI applications used by more than 125 million users globally. That operational foundation has informed the design of R10, particularly in ensuring consistency, reliability, and execution under production conditions.

The accessibility dimension of the award highlights another layer of significance.

In markets such as India, the primary barrier to digital adoption is often not access, but usability. AI systems that can simplify interactions and complete tasks on behalf of users have the potential to extend access to services at scale—moving beyond interfaces to outcomes.

This is where the next phase of enterprise AI appears to be heading.

From intelligence layers to execution systems. From pilots to production. From interfaces to outcomes.

And in that shift, the question is no longer whether AI can respond—but whether it can reliably act.