Please welcome Snowflake Chief Executive Officer Sridhar Ramaswamy.
Hello and welcome to our biggest and best Snowflake Summit ever. Over 20,000 of you here with us. Over 500 sessions, almost 700 speakers from 350 organizations. Thank you all for being here with us. I may be a little biased, but I think we have truly the best community in the world right here. And we're here because of all of you. This incredible group of customers and partners and Snowflakes who motivate us to go further faster. I want to take a moment to thank the thousands of customers here with us. Thank you. You're shaping the future of data and AI and we're super proud to be your partner. Thank you.
And we have hundreds upon hundreds of partners right here today. These are the organizations that are supporting Summit. They are the ones that are working together with our customers to show what is possible with AI and data. And finally to our Snowflakes. This week comes to life because of you. Every demo, every launch, every unforgettable moment reflects the incredible work that you put in every day. Thank you.
This week is going to be opening up the realm of possibility. Last year, we could not have imagined some of the things that we are doing right today. We have customers like Canva, one of the largest design platforms on the planet with an eye-popping 265 million people showing up every month to create. And last year, they stood on this stage and shared how they're going to use Cortex Analyst to get more value from data faster. Fast forward a year from now and they're using Snowflake AI to transform how they make product decisions, turning weeks of analysis on user behavior and feature impact into near real-time insight. This enables their team to move faster, invest in new areas with confidence and deliver incredible experiences at the crazy scale that they operate in.
And then we have folks like Nestle. It's a global company with over 2,000 brands across 185 countries. We have Nestle fans. Let's give them a hand. And as part of their enterprise digital transformation, Nestle has embarked on an end-to-end reimagination enabled by data and AI. They've built enterprise products that are now deployed to over 50,000 users and have 150 global capabilities. But what does it do? It's driving greater interoperability, greater reuse of data, and they're using AI to help anticipate supply chain disruptions, giving planners the insight to respond to shifts in supply and demand and production across their global operations. This means that they're creating an operation where data isn't reporting on the news. It is driving proactive decisions in real time.
And overall, I have to tell you, and I'm sure there are many people here that feel like this, this is one of the most magical periods of technological change that I have personally ever seen. AI isn't a promise anymore. It's creating real outcomes, real tangible opportunity. And our goal this week is to make AI real for your business.
The very nature of work is changing. Increasingly day-to-day work is about partnering with and guiding intelligent agents. And soon they will be operating across your business continuously, autonomously. This truly is going to be the era of the agentic enterprise. That's a vision though. You have to make it a reality. How do we go about doing that? There are four essential components to becoming an agentic enterprise. First, you need to have your enterprise data and context. Your customers, your financials, your product data, everything that makes your business your business.
And then you need AI models. Cloud Opus, Llama, Gemini, GPT, these are the amazing models that interpret, reason, and act on your enterprise data and context to deliver meaningful insight. There's more. All the software and applications that you folks use that we all use every day. Gmail, Outlook, SAP, Salesforce, Zoom. These are the applications that we use to keep our businesses running. But there is a fourth component that brings this all together. And to be successful as an agentic enterprise, you need an agentic control plane. This is a mission control center to coordinate across your data models and applications to ensure that every decision and action is governed, trusted, and grounded in your business context.
And that is what Snowflake is delivering with Snowflake Intelligence and Cortex Code. For knowledge workers, Snowflake Intelligence is the personal work agent that helps you work smarter. With Snowflake Intelligence, you can access all the data you need, but take action across the applications that you use every day, but do it in natural language. And for builders, Cortex Code or Coco as we call it affectionately is the AI powered coding agent that helps builders tap into any data anywhere and build faster with confidence. You're able to turn ideas into working pipelines, applications, or agents. Again, all using natural language. These are the building blocks of a system of decision. These are your agentic control planes and they're already powering incredible transformation across thousands of leading enterprises. With agentic enterprise, things just look different. And here is a view of what this future looks like that we at Snowflake are living through.
Data shouldn't slow down your business. Hey, we're suddenly losing customers. What's happening?
I can set up a dashboard, but it's going to take me a while. When questions move faster than answers, you need AI that breaks silos and adds context.
The largest driver is onboarding delays. What can we do about it?
Let's find out.
Allowing you to get answers quickly to make decisions and take action.
Now, here's what we automate next. Early churn signals, triggered interventions, proactive outreach.
I've already built a skill with Coco so we can self-serve across the team.
In the Agentic Enterprise, everyone becomes a strategic force shaping what the business does next.
And what do we want to talk about and help you all do? Bring that vision into a reality for you, all the people in this room that are going to be driving this transformation in your companies. Now, I'm sure you're thinking, 'Uh, that sounds easier said than done.' But we at Snowflake are here to help you get there. We work across all four of these components to make this coordinated action possible. Let's break down the journey. This agentic enterprise. Of course, all of this starts with your enterprise data and context. The foundation. We hear it constantly from all of you. Our data is a mess. There's more of it than ever before. Structured, unstructured. It's not working for our business. It's not yet ready for AI. That's a heck of an expensive gap. Why? Because your data is your most defensible moat. It's what makes your company truly your company. It's the foundational context that make AI outputs relevant, differentiated, and strategically valuable for you. If it's sitting fragmented and unused, so is your competitive edge.
So, why isn't your data ready? We ask you. And if you ask anyone that's tried to build a data pipeline, they'll all tell you the same thing. Data siloed across applications, across a dozen systems, multiple cloud providers, legacy platforms, each with its own format, each with its own source sliced version of the truth. And bringing all of this together has been this painful, difficult problem. It's a never quite finished engineering problem. Snowflake is here to help you unify your data and break down those silos. We make it easy to get data into Snowflake through seamless AI-powered migrations, Postgres support and OpenFlow for continuous data movement. We make it easy for you to share your data across teams even with partners using solutions like data clean rooms and we support you in your full data journey in one platform. From migrations to lakehouse and analytics to AI-powered BI all in a single place.
But bringing data together is only part of this challenge. You also need to make that data enterprise ready. That means you need to have governance. You need to have security. You need to have auditability and compliance built from day one, not bolted on later. Because we've been built for the enterprise from the very beginning, organizations can rely on the resiliency and business continuity controls that they depend on. Knowing that only the right people can access the right data, we offer you the flexibility to operate across cloud providers and model providers. We are also open and interoperable so you can work with the systems, tools and technologies of your choice. And with governance, security and compliance embedded into the platform from the start, your data isn't just unified. It is trusted and ready for AI. And that's what it takes to unlock performance from your data at massive scale.
And now with Coco, the work of getting there just got dramatically faster. That never quite finished engineering problem, it's now automated with Coco. Migrations can be done in days. Pipelines are built autonomously. And now all of you can spend your time on higher level strategic work. Setting a strong enterprise context foundation moving towards autonomous workflows. That's step number one in becoming an agentic enterprise.
And few have moved faster or helped more companies do the same than Accenture. They've not only advanced their own data and AI strategy, they've helped thousands of customers do the same. They're a leader showing up how you can make AI real for your enterprise. And let's hear from someone who sees AI's impact play out across every industry, every market, and every kind of enterprise. Let's hear from Julie, chair and CEO of Accenture.
Thank you, Sridhar. And hello, everyone. You've just heard Sridhar describe how the agentic enterprise will define the next phase of work. It is the daily conversation for me and my leadership team. Every client is asking the same question. How do we move from AI ambition to actual business outcomes? And here is what we tell them. AI is a powerful tool. It creates real value when humans are in the lead. That means leaders knowing how it's used, where it's trusted, and which outcomes matter most. When leaders take personal responsibility, AI opens up entirely new growth. And that hands-on responsibility starts with leaders changing how they work themselves. If as a leader you don't understand AI, you can't explain it. And if you can't explain it, you can't reinvent how work gets done with your teams. Scaling AI takes leader-led adoption, a decision to reinvent that inspires as much as it informs. And reinvention only lasts if it shows up in the P&L. Every pilot looks promising on a slide. What matters is whether AI is embedded in how the enterprise actually runs with clear accountability and ownership. That is when impact gets real and durable. As Sridhar said, the Agentic Enterprise is built on data, strong, trusted, governed data. That is why our partnership matters. Together, we help clients put the data foundations, controls, and governance in place to move past the insights and into outcomes at scale. It has never been more important to get this right. You will hear more now from Anish Charma who leads our reinvention services on how we're bringing this to life together. Thank you.
Thank you Julie. Please welcome Manish Sharma, Chief Strategy and Services Officer of Accenture to the stage. Manish, thank you for being with us. This is quite the crowd.
Well, Manish, you are at the forefront of transforming Accenture, which is a sizable organization, into becoming an agentic enterprise. How are you turning that vision for where you want to go into the reality of what needs to get done?
I think first of all let me kind of just say incredible event like just even before it is started just meeting the folks around the buzz it is incredible so thanks for organizing thanks for having us here and we love this partnership and I want to start by saying congratulations on the strong momentum on the Snowflake intelligence as well as the Cortex Code it has been incredible what we are seeing in the market and with our clients and with ourselves.
That's right. That's right.
So I think in terms of what we are doing in Accenture, I think two months back virtually we changed every single job in Accenture of a 70 billion company 750,000 folks across the world. We kind of organized every single job 750,000 people?
You know and we created it across seven key personas like whether it is CFO CHRO supply chain and manufacturing which is the customer part but each one of them required a strong data foundation so we have organized Sridhar on what we have been always been discussing but we reorganized just to ensure that we are able to facilitate and reinvent ourselves every single process, every single business outcome that we need to deliver based on a strong data foundation working with you.
That's right. That's right. That's right. In fact, I remember talking to Manish. I think it was early January when I showed him what was possible with Snowflake Intelligence and he gave me a glimpse of what they had already built on their data foundation on top of Snowflake and we went to work making that data come alive for Julie and Manish and everyone else and that told us a lot which brings me to my next question. How has AI changed how you operate day-to-day and how do you use that to inform what your customers should do?
So I think right now we are doing at scale across the globe with thousands of clients but every time Sridhar and the team comes to us with something brilliant and he's always got to show me something on his mobile you know and he's fascinating whenever we talk to him the first thing we want to do is apply it on Accenture because if you can do it in Accenture with our complexity with 57 countries 750,000 people thousands of clients. We have 9,000 clients across the world. You can do it anywhere.
So the first one is always customer zero. So we built and most of our clients AI is not the challenge. The challenge is the data and the process debt that people have.
85% of our clients have a data problem.
And that is where we come and partner with you. And in our case, we built our the full data foundation is built on your stack.
You know, everything we have tried before, we have gone to every single client. I remember there was one very large wealth advisory financial services company and we were going there and it's the messiest the most legacy stuff and you know you will get frightened to kind of just see the different data structures and the data stuff that they have fragmented we went with you sorted it and now we are getting insights so quickly that I can't even imagine three or four years back that we could have done this but that is again to the strong partnership that we have with Snowflake.
And that's the magic of the moment. What are you most excited about what we can unlock for our customers together say in the next two quarters?
I would say relentless focus on business outcomes relentless focus on linking every project you do to a line item of your P&L. Is it impacting your revenue, is it impacting your COGS or is it impacting your SG&A. Got to have clear linkage create value. And I'll give two examples one of them is one of my favorites. A utility company again a legacy European utility company we went there together and billions of data elements. What is the outcome? An analyst wanted to query from taking weeks to 2 seconds. That is exact stat. From scope of a project to actual execution of the project 12 weeks from months. Compute time down by 85%.
That is kind of the one piece.
The other one which again is a client which I'm personally involved manufacturing client US. I thought I can never get in every meeting you start there they will first argue for first half an hour about whether the data is correct or not correct and whose data is right and creating a single source of truth among huge number of fragmented systems and data records. Now we have one single source of truth. Ability to have decisions faster, much quicker. Incredible. And I think if I were to kind of just tell the folks here, that is what we should be looking at. Relentless focus on business outcomes linked to your line item. Don't do a project if you are not linking it to business outcomes.
There's a simplicity and beauty to all of this which is we succeed when we help our customers make more money or spend less money.
Either I mean use COGS or SG&A there is nothing more than that right.
That is that is that is amazing it's also such crystal clear just clarity on how to work I want to thank you again for and Julie for the partnership our teams work extraordinarily well together and we are transforming ourselves and I could not be more thrilled to have a partner like you thank you.
And we will create more and more value for our customers and clients every single day thank you thank you for everything.
Thank you for being here.
What Accenture shows us is that organizations winning with AI are doing it by connecting AI to what they actually know, their customers, their operations, their data, but also a clear hard-eyed view of what value creation means. So that was the first big step in this journey. So you have a strong enterprise context foundation. How then do you create meaningful insight for your business? And this is where AI models enter the conversation. Just the pace of innovation with AI models has been nothing short of stunning.
There is a but to that. The model is not your unique advantage. Why? Because your competitor has that model too. It is when you combine that model with what is uniquely yours, your data, which is your advantage, that things begin to shine. Your customer data, your operational and performance data, your partner data, your application data, all of the proprietary context. That's what makes AI useful for your business. So then the challenge becomes enabling models to reason over the full context of your enterprise.
And Snowflake has always been about choice, and that extends to models and to providers. One workload may benefit from a frontier model that's built for broad reasoning and exploration, while another might be better served by an open source model that's optimized for speed, customization, or cost efficiency. Through native partnerships with amazing model providers like Anthropic and OpenAI, Snowflake gives you flexibility to choose the right model for each use case. Instead of moving data to the model, you bring AI directly to your data with the freedom to switch, combine, and evolve models as your needs change.
And we help connect the intelligence to the applications and systems that your business runs on. Snowflake has always been about zero-copy integrations with applications and systems that you use like SAP, Salesforce, ServiceNow, Workday, IBM, and many more. So you can tap into all of your data without moving or copying it. And traditionally integrating applications connecting them has required complex brittle integrations. MCP, which is a protocol pioneered by Anthropic changes that. It's an open standard. It gives AI systems a simpler way to connect with the applications and platforms that all of you use every day. But you know what? In the enterprise, connectivity alone isn't enough. It obviously has to be secure. It has to be trusted. It has to be governed.
And that's why we have announced our intent to acquire NATTO. With NATTO, Snowflake is bringing MCP-powered connectivity natively into the AI Data Cloud. All of the applications that you folks use whether it is Google Drive or Gmail, Zoom, Jira, Slack, GitHub, Microsoft 365, these all are now visible to AI models and every interaction with these applications will be governed by Snowflake's security and access controls, giving organizations visibility, oversight, and safeguards such as human-in-the-loop approval. And this expands Snowflake's governance perimeter from data to AI action and workflows across the enterprise because the future of AI isn't just getting an answer. It's about turning fragmented systems into actionable insight.
But of course, the next question that you will have is how do you turn these insights into actions that you can take? How can you start executing complex agentic workflows? How can you operate at the speed of AI? And this is where there is a new category called the agentic control plane that is becoming essential. You can spin up agents across your business, but without a control plane, these agents are effective only in isolation, but they're not really aware of each other. An agent in finance can make assumptions that contradict what the supply chain agent just decided. And a marketing agent might generate content without knowing what a support agent learned about that customer just minutes before. You need a way to coordinate across your context, models, and applications so that decisions and actions happen seamlessly across your business. And Snowflake is helping thousands of businesses do just that.
With Snowflake Intelligence, every user in your business now has a personalized work agent, a single place to access data and take action. Whether it is sending a Slack, summarizing meetings, searching across email threads, the things that you do every day, all automated, all governed. And now those agents can even be equipped with specialized skills built around how your teams actually work and able to take action within these workflows.
An HR professional shouldn't have to ask a generic AI assistant for help with recruiting. They need to have a skill that knows their candidate pipeline, can talk to that application, talk to other tools and their processes and can then act on it. Similarly, a sales leader that's planning for the quarter needs more than a chatbot. They need a skill that pulls their forecast, surfaces potential risk, and drafts the prep deck for the meeting without being asked to do that twice. And a marketer personalizing an email campaign shouldn't be copying and pasting between tools. Their skill already should do that because they already use it. And it should bring together these things into Slack, Salesforce, Google Workspace, Microsoft Teams, whatever products that that particular company uses. And that becomes the difference between an AI that gives you answers and AI that can turn that answer and insight into action in the applications that you're using day-to-day.
And for all of you builders out there, developers, data engineers, analysts in your organization, we give you Cortex Code which we affectionately call Coco. With Coco, you can build anything. It lets you go from idea to working system using simple natural language. With Coco, a migration that took 6 months now is 6 days. It can assess the workload, convert the code, validate it, and deploy it all in a conversation. You can build complex pipelines, dynamic tables, quality checks, governance, data cost, cost monitoring in one afternoon. You can stand up a production application connected to live data before lunch. And Coco just doesn't write code. It understands your Snowflake environment, your tables, your roles, your security boundaries. It builds, tests, deploys, and optimizes. And it learns continuously. The thing that used to require a specialist in your team now just requires an idea.
And it's amazing to see how quickly Snowflake Intelligence and Coco are changing the way enterprises work. Sanofi has been at the forefront of this agentic transformation building a strong data foundation and reimagining how work gets done across the company for the AI era. They were prescient folks. They started this years ago and I'm really thrilled that they're here today to share their story. Please welcome Emmanuel Frenard, executive vice president and chief digital officer of Sanofi to the stage.
Thank you. Thank you for having me. What an intimate setting.
Gosh, I love your t-shirt.
Thank you. Yeah, I went all in.
Well, I think we should start by giving folks an idea of the scale that you folks operate in. You operate across R&D, manufacturing, commercial, and all of it is powered by data. Take a step back and walk us through the early steps that you took to become an AI native company.
So we have to roll time back five years. Before we engaged with Snowflake, we had...
Pre-GPT we had many data lakes. To be honest, they were data dumps and we went all in with Snowflake because we saw that bringing the cohesion or the continuum of data was a necessity for us in a industry where you do drug development, drug discovery for patients, you need the data continuum. And what we really liked about Snowflake was the separation you had between compute and storage that was powerful for us but let's be honest Sridhar while we consolidated massive fragmentation on Snowflake really what we got out of it were thousands of PowerBI dashboards and so the power of the data was still untapped.
Well, so we will come to that. But even in that early journey, you chose us as a partner which we are very grateful for. Can you talk a little bit about like how you decided to partner with us as you embark on the AI journey of how do I actually get value from all of the work that you did with data?
Well, you had a little role to play in this yourself. I think the reality was the commitment you've made and the joint partnership that we created.
That's right. That's right.
And then we tapped into one of your hidden powers, your forward-deployed engineers. They're embedded in our teams. They live and breathe our problems and they truly are some of the best talent we've ever worked with. So I'm going to take this small stage to do a shout out to Vivek, Love, Mac, Tyler, Ashkin, Way and your teams who are just outstanding and I'm sure I'm missing some.
Well, thank you. I remember talking to your team when I was in Toronto. I met with all of the folks in one of the data teams. It was an inspiring conversation. They were so keen to learn more and do more. A lot of folks talk about the transformation to becoming an agentic enterprise. You're one of the few folks that has actually done this transformation across multiple departments within Sanofi. Give us some examples.
So we haven't done it alone. We've done it with yourselves and a company called Elementum.
