Snowflake Intelligence and Data Science Agent Deliver The Next Frontier of Data Agents for Enterprise AI and ML
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Business users can now harness AI data agents to analyze, understand, and act on structured and unstructured data with
Snowflake Intelligence, without technical overhead - Data scientists can leverageData Science Agent to automate their ML workflows, boost productivity, and accelerate time-to-production for ML use cases
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Over 5,200 customers from companies like BlackRock, Luminate, and
Penske Logistics are using Snowflake to deploy AI solutions across their businesses
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Business users can now harness AI data agents to analyze, understand, and act on structured and unstructured data with Snowflake Intelligence, without technical overhead
Snowflake Intelligence (public preview soon) offers business users and data professionals a unified conversational experience — powered by intelligent data agents — to ask natural language questions and instantly uncover actionable insights from both structured tables and unstructured documents. Snowflake is also unveiling Data Science Agent (private preview soon), an agentic companion that boosts data scientists’ productivity by automating routine ML model development tasks. These innovations enable users to simplify their AI and ML workflows, democratize access to data across their businesses, and eliminate the technical overhead that slows down business decision-making — all through natural language interactions within Snowflake.
“AI agents are a major leap from traditional automation or chatbots, but in order to deploy them at scale, businesses need an AI-ready information ecosystem. This means enterprises must be able to unite data silos, maintain enterprise-grade security and compliance, and have easy ways to adopt and build agents," said
“At WHOOP, our mission is to unlock human performance and healthspan, and data is central to everything we do. Snowflake Intelligence marks a big step forward in our ability to be a data-first organization, ensuring that all employees can access insights without relying on analytics teams as the intermediary,” said
Snowflake Intelligence Reimagines Business Intelligence, Without the Overhead
Today, organizations are plagued by inefficient decision-making due to disjointed data governance, silos between data formats, and a shortage of technical data analysts who can code and synthesize information across the business. Snowflake Intelligence eliminates these operational challenges, allowing non-technical users and business teams to have conversations with their enterprise data in natural language — all without writing a single line of code.
Running directly inside organizations’ existing Snowflake environment, Snowflake Intelligence inherits all security controls, data masking, and governance policies automatically. It unifies data across sources including Snowflake, Box,
Snowflake Intelligence is powered by state-of-the-art large language models from Anthropic and
“By integrating Claude's reasoning capabilities directly into Snowflake's platform, we're further eliminating the traditional barriers between data and insights. Business users can now have natural conversations with their enterprise data, while data scientists can automate complex ML workflows — all through simple natural language interactions,” said
Data Science Agent Automates Tedious ML Tasks, Saving Hours of Manual Work
Data scientists spend lengthy cycles on developing and troubleshooting their ML workflows, leading to operational bottlenecks and fewer ML models making their way to production. Now, Snowflake is bringing agentic AI to ML workflows with Data Science Agent to boost productivity for ML teams by slashing hours of manual work.
Data Science Agent uses Anthropic’s Claude to break down problems associated with ML workflows into distinct steps, such as data analysis, data preparation, feature engineering, and training. Combining advanced techniques such as multi-step reasoning, contextual understanding, and action execution, Data Science Agent provides verified solutions in the form of fully functional ML pipelines that can be easily executed from a Snowflake Notebook. With suggested improvements, or with user provided follow-ups, Data Science Agent helps users easily iterate to the next-best version. By automating this tedious work, data science teams save hours of time that they would typically spend on experimentation or debugging — and can instead focus on higher-impact initiatives.
Snowflake Accelerates Enterprise AI Adoption for More Than 5,200 Customers
Today, over 5,200¹ customers from companies like BlackRock, Luminate, and
Learn More:
- Double click into how Snowflake Intelligence is democratizing access to data in this blog post.
- Read more about how Snowflake is making it faster and easier to build and deploy agentic AI apps on enterprise data in this blog post.
- Learn more about how global organizations can get started with AI data agents today and define an ROI framework to measure business impact in this A Practical Guide to AI Agents ebook.
- Check out all the innovations and announcements coming out of Snowflake Summit 2025 on Snowflake’s Newsroom.
- Stay on top of the latest news and announcements from Snowflake on LinkedIn and X, and follow along at #SnowflakeSummit.
1. As of
Forward Looking Statements
This press release contains express and implied forward-looking statements, including statements regarding (i) Snowflake’s business strategy, (ii) Snowflake’s products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, and (iv) the integration, interoperability, and availability of Snowflake’s products with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading “Risk Factors” and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the
© 2025
About Snowflake
Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 11,000 companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to build, use, and share data, apps and AI. With Snowflake, data and AI are transformative for everyone. Learn more at snowflake.com (NYSE: SNOW).
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