Snowflake, the AI Data Cloud company, convened customers, partners and technology leaders at Snowflake World Tour Mumbai to discuss how organizations are moving from AI experimentation to enterprise-wide deployment, with an increasing focus on trust, governance, data readiness and cost control. The event followed Snowflake‘s recent announcement of Dynamic Model Routing in Cortex AI Gateway, which strengthens the company’s vision for the Agentic Enterprise by enabling organizations to intelligently optimize model selection, improve AI economics and maximize business value from AI investments.
From AI Experimentation to AI Economics
At the heart of the event was Snowflake‘s commitment to helping organizations build a foundation for enterprise AI. During his keynote, Vijayant Rai, Managing Director- India, Snowflake, emphasized that successful AI adoption depends on the quality, context, accessibility and governance of enterprise data.
“AI is everywhere, but context isn’t. Context is what makes AI dependable, relevant, and capable of delivering business value at scale,” Rai said, underscoring the critical role of trusted and governed data in enabling enterprise AI. He noted that while organizations have invested heavily in AI experimentation, the next phase of adoption will be defined by how effectively AI systems can access trusted data, business context and operational workflows.
Over the last year, organizations focused on pilots, proofs of concept and model experimentation. Today, leaders are increasingly asking how AI can be deployed responsibly and economically at scale. As AI adoption grows, concerns around model costs, token consumption, governance and operational complexity are becoming just as important as model performance. Snowflake emphasized that the next phase of enterprise AI will be defined by balancing innovation with trust, control and cost efficiency.
Building the Control Plane for the Agentic Enterprise
Snowflake reinforced its vision of becoming the control plane for the Agentic Enterprise, enabling organizations to govern how AI agents interact with enterprise data, applications and models.
The company outlined three foundational capabilities that underpin this vision:
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Enterprise Data & Context: Snowflake highlighted innovations such as Horizon Context, which embeds business meaning and semantic understanding directly into enterprise data. By grounding AI in trusted data and shared business context, organizations can deliver more accurate, consistent and reliable outcomes across teams and applications.
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AI Model Choice: Snowflake reiterated its model-agnostic approach, enabling customers to leverage both frontier and open-source models while maintaining governance and flexibility. Rather than routing every workload to the largest and most expensive models, organizations can optimize costs and performance by matching the right model to the right task, helping improve AI economics without sacrificing outcomes.
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Software & Applications: Snowflake showcased how organizations can connect AI directly into business applications and workflows without moving or duplicating data. The company also highlighted innovations such as Snowflake CoCo and CoWork, designed to help developers and business users build and interact with AI-powered applications within a governed environment.
Building on Snowflake‘s recent announcements around the trusted agentic enterprise, the company showcased capabilities including Cortex AI Gateway, designed to provide centralized visibility, governance and cost controls across AI agents, models and workloads. The solution enables enterprises to monitor AI usage, govern access to data and applications, and better manage AI-related spend as adoption scales across the organization.
Recognizing India’s Data Leaders
The event also celebrated the Snowflake Data Driver Awards, recognizing organizations and leaders that are driving business impact through data and AI. Jubilant FoodWorks received the Data Driver of the Year award, SMFG Credit was recognized for Innovation in Data Analytics, and Nishant Pradhan, Chief AI Officer at Mirae Asset Investment Managers (India), was named Data Executive of the Year.
The Road Ahead: Maximizing ROI for AI
Rai concluded by reiterating that the future of enterprise AI will be determined not by model sophistication alone, but by the ability to combine trusted data, business context, model flexibility, governance and cost efficiency at scale.
As organizations across India accelerate AI investments, the message from Snowflake World Tour Mumbai was clear: the era of the Agentic Enterprise is here, and enterprises that can combine trusted data, context and AI with governance and cost control will be best positioned to lead in the next phase of AI-driven transformation.