Agentic Infrastructure: The Next Leap for India’s SaaS & Deep Tech Startups

How autonomous agents will reshape platform engineering, deployment, and scalability Agentic AI is the next major workload shift which is driving the next generation of cloud infrastructure. This time, India can build it. Together, the agentic SaaS layer and the sovereign infrastructure underneath give Indian companies the foundation to compete with the West and with China, in domestic markets first and global markets next. This time, India should be the builder. Three constraints are loosening at once. AI-augmented engineering has reset the cost of building software. One engineer now delivers in a quarter what 3 engineers used to ship in a year. The senior engineering leaders who built the world’s largest cloud and AI platforms are starting to return to India driven by uncertainty in the US and a maturing domestic ecosystem that now offers hard problems and real capital. And the dominant AI workload is being rebuilt around agents, a category no incumbent yet owns. Inference workloads dominated AI through 2024: stateless, latency-sensitive, sub-second requests. Agentic workloads dominate from 2025 onward: long-running, stateful, tool-calling, and cost-bursty. The serving stack built for the first has to be re-architected for the second. The rebuild that follows opens two parallel opportunities for Indian startups: the SaaS layer above the model where agentic applications meet enterprise problems, and the  underlying infrastructure layer below that has to be purpose-built for these workloads. Both represent a strong opportunity for India. The application layer is where AI moves from research to revenue, and Indian SaaS is positioned to capture a large share of it. Five workload categories are in production today. Voice agents are replacing first-line customer support and collections at scale, with Indian companies like Skit.ai, Vodex, and Bhashini-powered platforms in production across BFSI, telecom, and healthcare. Customer support automation through agents that triage, resolve, and escalate is the default at Freshworks Freddy, Zoho Zia, and Sprinklr. Service and technical support is being rebuilt around agents that read system logs, run diagnostic tools, and resolve incidents, with Indian platforms like Yellow.ai, Atomicwork, and Gnani.ai deploying these capabilities to IT helpdesks, application support, and field operations. Back office automation across invoice processing, expense reconciliation, KYC verification, and vendor onboarding is being rebuilt around agents that work across systems of record. Self-service in HR, procurement, and finance is moving from rule-based chatbots to agents with memory and tool access that close tickets autonomously. India’s SaaS market is on track to cross $50 billion by 2030, and India runs a sizeable share of the world’s customer support operations. Indian SaaS players like Zoho, Freshworks, Postman, and Razorpay have shipped AI features into enterprise workflows at scale and are now adding agentic flows on

Original source: The Tech Panda