As 2026 approaches, startups face a reset moment—one where speed alone is no longer a differentiator, and trust, data-readiness, and capital discipline take center stage. In a Snowflake panel discussion titled ‘Future-ready Startups: Data, Product Innovation & Capital Strategy for 2026’, leaders from infrastructure, enterprise AI, fintech, and venture capital came together to map what’s next, outlining the transformative changes driven by AI, the importance of compliance, data security, and the role of startups in addressing these challenges.
Panel discussion participants includedPrashant Muddu, Managing Director and CEO, Jocata; Srikanth Gaddam, Co-founder, Stealth Startup; Srikanth Tanikella, Managing Partner, Pavestone VC;Kalyan Muppaneni, Founder, Chairman & CEO at Pi DATACENTERS and Sumeet Tandure, Senior SE Manager, Snowflake. The roundtable was moderated by Rishabh Mansur, Head – Content Categories, YourStory.
The startup shift in 2026: what to expect
Kalyan Muppaneni, Founder, Chairman and CEO at Pi DATACENTERS, opened the discussion, sharing his thoughts about the nationwide expansion of edge and micro data centers. He spotlighted Pi’s pioneering move into Tier II and Tier III cities, delivering uptime beyond traditional hubs like Mumbai and Chennai. This move decentralizes capacity to meet growing outsourcing and cloud demands across India’s diverse geography. Srikanth Gaddam, ex-CTO at Zaggle and now co-founder of a stealth startup, highlighted the importance of data-driven decision-making frameworks. With AI accelerating builds at lower costs, he warned against wasteful experimentation, saying ”Earlier, the cost of building was higher, so we used to take our time. Now that costs have reduced its faster. How do we avoid this? How do I enable every decision maker to take the right decisions, handle product innovation, AI experiments, or even deploy capital? We need to connect these processes with the right decision-making framework and make the data as a foundation for that.”
Prashant Muddu, Managing Director and CEO at Jocata, anticipated how product companies will embed AI natively rather than as a simple bolt-on. Jocata is planning a full rethink over the next 12-18 months to retool platforms for regulated sectors such as credit decisioning and financial crime compliance. According to Muddu, AI services will falter long term, making core integration essential for clients in high-stakes banking environments.
In 2026, Srikanth Tanikella, Managing Partner at Pavestone VC, expects investors to prioritize AI-native or AI-immersed enterprise solutions. Post-ChatGPT, plain SaaS pitches have failed without AI. Enterprises now have to prove how they can leverage AI effectively. “We shifted our game saying that unless and until you are either an AI native entity selling a product to large enterprises, or you have started to build AI into your product, making it an AI immersed solution, even if it’s not AI native, we wouldn’t really be able to support investment any further.” Pavestone is doubling down on deep tech, bolstered by government RDI funds for patient capital, shifting from sticky enterprise tech to AI-centric models.
Sumeet Tandure, Senior SE Manager at Snowflake, outlined the shift to industry-specific AI solutions atop clean data infrastructure. “We began to go after industry use cases where AI becomes a part of the overall solution, and not just the cream on top,” he said. Furthermore, he spoke about Snowflake’s pivot with Cortex to build AI without complex pipelines. With LLMs becoming cheaper and more affordable, the company focused on unique industry use cases to create a strong edge. Teams now prioritize fast demos using database objects like Cursor to quickly show value in safe, secure setups.
What the future looks like for data security
Data regulation is crucial in 2026 to combat surging digital fraud, protect personal privacy, and ensure trust in AI-driven systems. According to Muppaneni, India's evolving data regulations are a positive shift ( though late compared to the US and Europe). The DPDP law now governs personal data sharing, cross-border transfers, and mandates local copies, boosting data center relevance amid RBI norms for backups, disaster recovery, audits, and downtime reporting in finance. However, he spotlighted a critical risk in the free flow of social media data across borders, emphasizing the need for tighter enforcement in the next two to three years.
Gaddam, on the other hand, highlighted the rising digital fraud costs in India, with Rs 24,835 crores lost from 2024-2025 to scams and payment links. He shared how victims suffer directly, organizations invest heavily in storage security and audits, and leaked funds fuel illegal activities like drugs and trafficking.
“The government has mandated that all companies, not just regular entities, must become DPDP compliant by May 2027. So I think things are moving in the right direction. More regulation will come, and companies have to take the responsibility to build trust – for both B2Bs and B2Cs,” he shared.
Agentic AI and the question of latency
In 2026, Agentic AI and low latency will be critical for Indian startups, allowing them to scale beyond pilots into production and driving efficiency in a booming market.
According to Tandure, Agentic AI will require non-negotiable trust, safety, and compliance. Without trust and safety and context, AI yields no real outcomes. If the source data is wrong, answers will be wrong too. Tandure advised startups to ground responses in truthful, privacy-compliant data. Use access controls to ensure users get only entitled information. These practices form the fundamental pillar for agentic AI.
Tandure also noted unresolved challenges when it comes to agentic AI, especially latency in multi-system interactions. However, researchers at Snowflake have been working on delivering fast and interactive responses, to cut down on latency. “One of the ways to do it is similar to having mirrors in elevators so that people don’t get bored. It's the same when agents are providing answers. Can you provide explanations during the wait so people understand what is happening? These are some creative ways to address the latency equation today,” he said.
Gaddam shared his belief that the issue of latency comes down to cost. In instances where companies can afford to have latency, creative tricks such as Tandure mentioned above, will smooth the process, covering a waiting period of about 12-20 seconds. Scenarios where latency cannot be permitted will push enterprises to solve the problem no matter the cost.“Ultimately, the issue of latency is a function of economics,” he said.
Funding opportunities in 2026
Government opportunities and funding will profoundly boost Indian startups in 2026 by providing scale, capital, and validation amid AI growth.
Muddu detailed the immense government opportunities for startups, which offer unparalleled distribution and growth for pilots that scale post-success. He contrasted India's government-led public infrastructure (e.g., UPI) with China's private-first model, advocating India's approach at global forums like the UN.
“In China, everything is built privately first before the government steps up. In India, the government moves first. They’ve created the public infrastructure for us to innovate. Two very divergent models, both working at scale. So, it becomes a philosophical question. What is the role of the government to provide digital infrastructure? How much and what exactly do they need to provide? Just like hospitals and police stations, what should be the equivalent of providing digital infrastructure. I think India’s model works for us,” he shared.
Tanikella noted VC proliferation in AI and deeptech, from family offices to stage-specific funds. He spoke at length about the government's Rs 1 lakh crore RDI fund that targets R&D-led innovation in physical AI, digitization, aerospace, and defense. Government-led funds such as the RDI fund, will be funnelled through VCs like Pavestone. He also advised startups in the prototype phase to look at focused research organizations for funding.
The discussion covered a range of topics, including strategic shifts for 2026 in the tech and fintech sectors, the need for data readiness, the importance of balancing innovation with regulatory compliance and much more.
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