Snowflake’s opening keynote set a new tone for Snowflake Summit 2025 – and theCUBE’s Rebecca Knight, Dave Vellante and George Gilbert break down every signal that matters. Broadcasting live from Moscone Center, the team dissects why this year’s 15K-strong gathering marks a decisive shift from cloud-native warehousing to an AI Data Cloudbuilt on open table formats, granular scaling and cost-savvy pricing.

Key takeaways include:
• Open, but still simple – Snowflake’s embrace of Apache Iceberg plus the open-source Polaris catalog synchronised with its proprietary Horizon layer shows how the company is making external data feel “Snowflake-native” without locking it in.
• Adaptive Compute & new pricing – Marriott’s on-stage debut of T-shirt-size-free “adaptive compute,” discounting Snowpipe by ~50 %, and a bring-your-own-compute option tackle the TCO gap for data-engineering workloads that had drifted to Databricks & Spark.
• Next-gen engine for AI era – A forthcoming engine upgrade, deeper Snowpark language support and plans to woo the data-science persona aim to keep pipelines, analytics and GenAI inference on one governed platform.
• Growth & competitive posture – With revenue tracking to $4 B and a $10 B north-star, Snowflake is betting that open standards, zero-copy sharing and multi-cloud optionality will secure its role as connective tissue for enterprise AI even as it eyes higher-order “knowledge graph” layers via partners like RelationalAI.
• LLM pragmatism – Integration paths for OpenAI, Anthropic and Mistral highlight a “choice with control” model that keeps sensitive enterprise data inside customer boundaries while unlocking text-to-SQL and agentic workflows.

Whether you’re sizing up Snowflake versus Databricks, planning AI workloads or mapping your data-governance strategy, this rapid-fire analysis arms you with the context behind the announcements – and the questions to ask next.

In this interview from Snowflake Summit 2025, Bibhu Patnaik, partner in Deloitte’s banking and capital markets practice, and Shailender Sidhu, partner and leader of Deloitte’s financial services Industry AI and data business, join theCUBE’s Dave Vellante and John Furrier to explore how data-driven disruption is reshaping financial services. The discussion spans today’s dual mandate of defensive compliance and offensive growth, revealing why forward-thinking banks are doubling down on AI-powered insights, agentic re-imagination and hyper-personalized customer experiences.

Patnaik and Sidhu unpack Deloitte’s Data as a Service strategy – built on Snowflake’s AI Data Cloud – to illustrate how zero-copy sharing, open standards and governed multi-cloud architectures accelerate everything from regulatory reporting to real-time product innovation. They share success stories where the Deloitte-Snowflake partnership has turned regulatory risk into a competitive advantage and scaled AI workloads across structured and unstructured data without compromising trust or control.

Looking ahead, the conversation examines the convergence of data engineering, DevOps and AI development on Snowflake; cost-governance tactics for large-scale models; and the emerging “Data for Good” initiatives driving mission-aligned innovation. Whether it’s next-gen AI apps built with Snowflake Cortex or future-ready analytics roadmaps for CFOs and CDOs, viewers gain a front-row seat to the strategies that will define data and analytics in FSI over the next five years.

In this interview from # Snowflake Summit 2025, Mona Chadha, director of category management at AWS, joins theCUBE’s co-hosts Dave Vellante and John Furrier to unpack how Snowflake and AWS are accelerating enterprise generative AI adoption on the AI Data Cloud. Chadha explains why an integrated Snowflake-on-AWS stack is becoming the connective tissue for building, scaling and governing intelligent systems – eliminating data movement while preserving strict security and cost controls.

The conversation dives into the nuts and bolts of putting gen AI into production. Chadha details how services such as Amazon Bedrock, Anthropic’s Claude and Snowflake Cortex combine with Apache Iceberg and low-latency streaming to create open, interoperable lakehouses. She highlights industry-specific blueprints – from Epic and SAP to composable CDPs – that are already delivering measurable outcomes, and shares customer success stories where multi-agent workflows and Q Business chatbots are boosting productivity without compromising governance.

Looking ahead, Chadha and the hosts explore what the next phase of the AWS-Snowflake partnership means for developers and data teams: zero-copy data sharing, multi-cloud flexibility and a growing catalog of managed AI services that let enterprises focus on innovation rather than plumbing. Whether it’s migrating legacy pipelines, orchestrating cross-platform AI agents, or activating unstructured data at scale, the message is clear – Snowflake and AWS together provide a friction-free path to transformational business value.

In this Snowflake Summit 2025 interview, Denise Persson CMO of Snowflake, and Mike Gannon, CRO of Snowflake, join theCUBE’s Dave Vellante and John Furrier for a fast-moving discussion on how the AI Data Cloud is reshaping go-to-market strategies. Broadcasting live from the show floor, they explain why Snowflake sees itself as the connective tissue for AI-driven innovation, data collaboration and operational efficiency across the enterprise.

Persson shares an inside look at Snowflake’s AI-driven playbook: using first-party data to personalize every customer touchpoint, optimize campaigns in real time and predict future demand. She outlines initiatives such as the Silicon Valley AI Hub, a $200 million Startup Accelerator and a $20 million global upskilling program – each designed to expand the AI talent pool and fuel the next wave of Snowflake-built applications.

Gannon details how Snowflake’s sales organization runs “Snowflake on Snowflake,” harnessing Cortex AI to surface insights that shorten deal cycles and quantify ROI for customers exploring gen AI. He discusses guiding enterprises through data governance and model explainability, plus activating a partner ecosystem that delivers thousands of AI solutions – leveraging open standards, zero-copy sharing and multi-cloud support to keep trust and control intact.

In this Snowflake Summit 2025 segment, Amit Sangani, who leads Meta’s AI platforms engineering team, and Dwarak Rajagopal of Snowflake AI research, join theCUBE’s Dave Vellante and John Furrier to explore how Snowflake and Meta are accelerating enterprise-grade generative AI. The conversation spotlights the strategic partnership that brings Meta’s open-source Llama models directly into Snowflake Cortex AI, giving customers a secure, zero-copy path to build, fine-tune and deploy AI workloads on the AI Data Cloud.

Sangani unpacks the recent Llama 4 release and the enterprise use cases where the model excels, from content generation to intelligent agents. Rajagopal shares how customers such as TripAdvisor are already tapping Llama inside Cortex AI to deliver personalized recommendations and richer user experiences. The duo explains why open-source models resonate with enterprises – offering ecosystem flexibility, vibrant community support and full ownership of fine-tuned weights – while detailing Snowflake’s built-in trust and safety guardrails.

The discussion also dives into Snowflake AI Research’s SwiftKV optimizations, which double Llama throughput on high-end GPUs and cut inference costs by up to 75%. Viewers will learn how these advances move Cortex beyond analytics to real-time, interactive AI and what’s next as data engineering, DevOps and AI development converge on Snowflake’s platform. It’s a must-watch for builders seeking efficient, governed pathways to scale AI across structured and unstructured data.