Demand for Narrow AI models is rising sharply, with startups such as Gnani AI, CoRover, Fractal Analytics and Meritto increasingly focusing on domain-specific systems built to perform clearly defined tasks with high accuracy. Unlike broad, general-purpose AI, Narrow AI is designed for specialist functions such as customer support automation, document interpretation, fraud detection and clinical analysis, making it attractive to sectors including banking, healthcare and education.
Predictability and Cost
Startups say enterprises are gravitating towards these specialist AI agents because they are easier to deploy, cheaper to run and simpler to regulate. “The model’s capabilities and risk surface are tightly bound, which makes deployment safer and more predictable,” Suraj Amonkar, chief AI research and platforms officer at Fractal Analytics, told Fe.
Sectoral Traction
Fractal’s Narrow AI portfolio includes Vaidya, a multimodal medical intelligence model built exclusively for healthcare, and Kalaido, a text-to-image diffusion engine focused on visual generation. Introduced last year, both systems reflect what the company sees as a clear shift away from experimentation with general-purpose AI. “We are seeing significantly higher demand across healthcare, digital content and enterprise workflows,” Amonkar said, adding that hospitals and diagnostics networks are increasingly seeking clinically reliable AI, while creators and small businesses are adopting cost-efficient image generation tools.
Gen AI platform CoRover has also seen strong traction for Narrow AI over the past year. “Teams now want focused tools for tasks like routing, call handling, document help and workflow checks,” Ankush Sabharwal, founder and CEO of CoRover, said. Clients, he said, prefer small, sharp models that run fast, cost less and fit easily into existing systems. The company offers purpose-built solutions for customer support, document processing, fraud detection and workflow prediction, designed to deliver consistent outcomes in real-world deployments.
Bengaluru-based Gnani AI reports similar momentum. “Enterprises running at least one narrow, production use case on our platform have grown more than 2x year on year,” Ganesh Gopalan, co-founder and CEO, said. Usage of narrow agents for collections, onboarding, renewals and support is growing faster than that of generic bots, he added, with most new deployments now focused on specific use cases. Narrow AI accounts for the bulk of the firm’s platform usage and pipeline momentum, delivered through its Inya.ai suite of voice-first models and pre-built agents.
In education, Info Edge-backed Meritto launched Mio AI earlier this year after observing that specialised agents outperform general systems in high-stakes workflows such as student enrollment. “What makes these agents narrow is not limitation, but precision,” Alok Sharma, senior vice-president of product at Meritto, said. Trained on real enrollment journeys and embedded into institutional workflows, these agents offer predictable, domain-deep intelligence. Sharma added that domain-specific Narrow AI also speeds adoption by reducing complexity for institutions.
Startups say the shift reflects a broader change in enterprise thinking. A year ago, organisations were largely experimenting with AI; today, discussions are more focused on outcomes, reliability and scale, driving sustained demand for Narrow AI systems.