Snowflake AI data cloud paves the way for India’s enterprise AI evolution
The final edition of the Snowflake World Tour in India, held in Mumbai, showcased how artificial intelligence (AI) and data transform India’s enterprise sector. Featuring insights from Vijayant Rai, Managing Director for India at Snowflake, and Prasanna Krishnan, Head of Collaboration and Horizon at Snowflake, the event showcased how the convergence of AI and data is enabling businesses across India by fostering innovation, efficiency, and growth.
Snowflake’s approach: Simplifying AI for Indian enterprises
“There is no AI strategy without a data strategy,” Rai highlighted in his keynote, emphasising the importance of a robust data framework for AI success. Above all, data should be securely accessible to the right people at the right time to make critical business decisions. Snowflake’s AI Data Cloud empowers organisations to unlock valuable data insights, enhance customer experiences, and minimise costs in industries such as financial services, retail and CPG, manufacturing, airlines and logistics.
Snowflake’s holistic approach to enterprise AI was evident through its core philosophy: delivering an integrated solution instead of isolated tools – “We give you the car, not the parts,” added Rai. By providing a unified platform, Snowflake helps enterprises overcome complexities, improve efficiency, and make AI implementation seamless and reliable.
Success stories: How Indian businesses are leveraging Snowflake
Snowflake’s AI Data Cloud has significantly transformed Indian enterprises, as highlighted by numerous success stories. Using Snowflake, Piramal Finance personalised products for the Bharat market and grew its business. Doing so resulted in 3x to 4x growth in data usage by its employees with over 100 business users actively using Snowflake, but the company still saved over INR 1 crore. Built on Snowflake’s platform, Razorpay’s DataSync service integrates business and financial data securely, allowing businesses to leverage it for better reporting, fraud monitoring, and generating new revenue streams, transforming payment data into a profit centre. Swiggy, the food delivery giant, has seen a 3.7x increase in daily queries, a 20% boost in data processing speed, and a 1.8x reduction in operational costs. Similarly, Urban Company improved operational efficiency tenfold, with query response times reduced from over 20 minutes to under 2 minutes, leading to quicker and more efficient decision-making. These examples reflect how Snowflake drives transformative change across industries, enabling advanced analytics, predictive insights, and personalised experiences for over 10,000 customers worldwide.
Prasanna Krishnan, in her address, said, “Snowflake is Data Complete,” says Prasanna. We can support organisations’ requirements for data types and architecture patterns. Snowflake has supported unstructured data for years, such as text, PDF, audio, images, and video files. Thousands of customers store and process unstructured data in Snowflake. This is even more critical now that AI allows organisations to derive more value from unstructured data. One example of the many ways to process unstructured data with Snowflake is Document AI.
Snowflake’s Document AI, available on AWS and Azure, helps business teams automate processes, gain valuable insights from their data and improve decision-making. The potential applications for this technology are vast — from small financial firms to manufacturing conglomerates, from invoice reconciliation to evidence discovery.
“The Snowflake AI Data Cloud is compute complete”, added Prasanna. It offers on-demand access to resources without delays, ensuring you only pay for what you use. Another key innovation is Snowpark Container Services, a fully managed container offering designed to facilitate the deployment, management, and scaling of containerised applications within the Snowflake ecosystem. Governance has been a differentiator for Snowflake since Day 1.
Snowflake Horizon Catalog offers a unified approach to compliance, privacy, security, and interoperability, including its support for Iceberg tables. This integrated platform helps businesses comply with various regulations, driving innovation at scale securely. Snowflake Horizon Catalog also underpins the secure sharing of data, applications, and models, facilitating the seamless integration of AI across organisations.
Further, thousands of customers are migrating spark pipelines written in Python, Java, and Scala to Snowpark, witnessing 4.6 times faster performance with 35% cost savings, making more than 50% of customers globally use Snowpark weekly.
Embracing future innovation: Gen AI, Cortex AI, and Arctic
Snowflake continues to focus on innovation through investments in Generative AI and the introduction of Cortex AI. Cortex is a fully managed service designed to democratise AI, allowing users to access top-tier LLMs and develop AI-driven solutions, regardless of technical expertise. This capability brings AI closer to governed data, ensuring easy access and governance for models. Additionally, Snowflake Arctic offers an enterprise-grade LLM optimised for complex tasks like SQL code generation and instruction-based processes, making it an ideal solution for handling challenging workloads.
Celebrating data-driven success
The event also honoured companies making strides in data-driven innovation through the Snowflake Data Driver Awards, honouring Graas.ai with the award for Data Collaboration.
Shaping the future of AI and data in India
In concluding remarks, Rai reiterated Snowflake’s vision of empowering enterprises with trusted, easy-to-use AI solutions, stating, “The era of enterprise AI in India has begun, and Snowflake is proud to be leading this revolution.” With a unified approach, a strong focus on innovation, and a commitment to security, Snowflake is helping Indian businesses harness the power of data and AI to transform their operations, fuel growth, and shape the future of enterprise AI in India.
