‘By definition, we’re competing with nobody’: Deloitte’s Nitin Kini on GenW.AI’s entry into product market

Deloitte India is preparing to launch GenW.AI, an indigenous, next-generation low-code platform designed to help enterprises rapidly prototype and deploy applications and AI agents at scale. The platform will be officially unveiled at the India AI Impact Summit in New Delhi next week.

Developed in India, GenW.AI brings together a full suite of tools under a single, unified architecture, which Nitin Kini describes as a first-of-its-kind offering in the domestic market. The platform is built to integrate with a wide range of LLMs, including open-source and enterprise-grade systems, giving organisations flexibility as sovereign AI ecosystems evolve.

Asked whether this positions Deloitte as a direct competitor to IT services firms, Kini said the opportunity lies not in competing head-on with traditional players, but in addressing “unserved and underserved problems.” “By definition, we are competing with nobody,” he said, arguing that the platform is designed for spaces yet to be fully addressed. While some overlap with existing product and services firms is inevitable, Kini maintained that no single player currently offers the breadth of capabilities GenW.AI brings together—workflow management, LLM-driven insights, dashboarding, SLA tracking and self-healing AI agents—within one platform.

At its core, GenW.AI is designed to mirror how enterprises function. Whether it is an IT managed services environment handling ticket workflows or an HR team screening CVs and tracking fulfilment ratios, the platform aims to combine automation and intelligence at scale. Its low-code framework is intended to accelerate development cycles, reduce dependence on large coding teams and enable faster deployment of use-case-specific solutions.

A key differentiator, according to Kini, is deployment flexibility. Available both on-premises and on the cloud, GenW.AI allows enterprises to retain full control over their intellectual property and data—addressing one of the biggest barriers to AI adoption. “Only about 11% of AI initiatives make it to production,” he noted, citing data security concerns and legacy system integration as major challenges. By supporting on-prem deployments and integration with existing enterprise technologies, the platform aims to reduce these frictions.

Cost efficiency is another focus. Kini said deploying popular AI tools at scale often leads to “bill shock.” For instance, equipping 45,000 employees with conventional solutions could cost an estimated Rs 125–130 crore, whereas Deloitte’s platform can achieve similar outcomes at less than 1% of that cost. The economics, he said, are driven by large-scale distribution and the use of proprietary technology in place of licensed products.

Deloitte has already piloted GenW.AI internally, training nearly 30,000 employees over six months. Client engagements are also underway, including hackathons with a large bank that generated more than 160 use cases.

While the initial focus is on financial services and government, the ambition is broader. Engineered to be “frugal enough for tier-two and scalable enough for the tip of the spear,” GenW.AI, Kini said, is designed for enterprises of all sizes, with the goal of making AI adoption friction-free across India’s business landscape.