Snowflake, the AI Data Cloud company has announced several product innovations at its annual user conference, Snowflake Summit 2025, designed to revolutionize how enterprises manage, analyze, and activate their data in the AI era. These announcements span data engineering, compute performance, analytics, and agentic AI capabilities, all aimed at helping organizations break down data silos and bridge the gap between enterprise data and business action — without sacrificing control, simplicity, or governance.

 

“With our latest announcements, we’re showcasing how Snowflake is fundamentally redefining what organizations can expect from a modern data platform,” said Vijayant Rai, Managing Director- India, Snowflake. “These innovations are focused on helping businesses make AI and machine learning workflows more easy, connected, and trusted for users of all abilities by democratizing access to data and eliminating the technical overhead that slows down business decision-making.”

 

Snowflake Openflow Unlocks Full Data Interoperability, Accelerating Data Movement for AI Innovation

 

Snowflake unveiled Snowflake Openflow, a multi-modal data ingestion service that allows users to connect to virtually any data source and drive value from any data architecture. Now generally available on AWS, Openflow eliminates fragmented data stacks and manual labor by unifying various types of data and formats, enabling customers to rapidly deploy AI-powered innovations.

 

Snowflake Openflow embraces open standards, so organizations can bring data integrations into a single, unified platform without vendor lock-in and with full support for architecture interoperability. Powered by Apache NiFi, an Apache Software Foundation project built to automate the flow of data between systems, Snowflake Openflow enables data engineers to build custom connectors in minutes and run them seamlessly on Snowflake’s managed platform.

 

With Snowflake Openflow, users can harness their data across the entire end-to-end data lifecycle, while adapting to evolving data standards and business demands. Hundreds of ready-to-use connectors and processors simplify and rapidly accelerate data integration from a broad range of data sources including Box, Google Ads,  Microsoft Dataverse, Microsoft SharePoint, Oracle, Proofpoint, ServiceNow, Workday, Zendesk, and more, to a wide array of destinations including cloud object stores and messaging platforms, not just Snowflake.

Snowflake Unveils Next Wave of Compute Innovations For Faster, More Efficient Warehouses and AI-Driven Data Governance

 

Snowflake announced the next evolution of compute innovations that deliver faster performance, enhanced usability, and stronger price-performance value — raising the bar for modern data infrastructure. This includes Standard Warehouse – Generation 2 (Gen2) (now generally available), an enhanced version of Snowflake’s virtual Standard Warehouse with next-generation hardware and additional enhancements to deliver 2.1x faster analytics performance and 1.9x faster analytics performance than Managed Spark.

 

Snowflake also introduced Snowflake Adaptive Compute (now in private preview), a new compute service that lowers the burden of resource management by maximizing efficiency through automatic resource sizing and sharing. Warehouses created using Adaptive Compute, known as Adaptive Warehouses, accelerate performance for users without driving up costs, ultimately redefining data management in the evolving AI landscape.

 

Snowflake Intelligence and Data Science Agent Deliver The Next Frontier of Data Agents for Enterprise AI and ML

 

Snowflake announced Snowflake Intelligence (public preview soon), which enables technical and non-technical users alike to ask natural language questions and instantly uncover actionable insights from both structured tables and unstructured documents. Snowflake Intelligence is powered by state-of-the-art large language models from Anthropic and OpenAI, running inside the secure Snowflake perimeter, and is powered by Cortex Agents (public preview) under the hood — all delivered through an intuitive, no-code interface that helps provide transparency and explainability.

 

Snowflake also unveiled Data Science Agent (private preview soon), an agentic companion that boosts data scientists’ productivity by automating routine ML model development tasks. 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.

 

Today, over 5,200 customers from companies like BlackRock, Luminate, and Penske Logistics are using Snowflake Cortex AI to transform their businesses.

 

Snowflake Introduces Cortex AISQL and SnowConvert AI: Analytics Rebuilt for the AI Era

 

Snowflake announced major innovations that expand on Snowflake Cortex AI, Snowflake’s suite of enterprise-grade AI capabilities, empowering global organizations to modernize their data analytics for today’s AI landscape. This includes SnowConvert AI, an agentic automation solution that accelerates migrations from legacy platforms to Snowflake. With SnowConvert AI, data professionals can modernize their data infrastructure faster, more cost-effectively, and with less manual effort.

 

Once data lands in Snowflake, Cortex AISQL (now in public preview) then brings generative AI directly into customers’ query engines, enabling teams to extract insights across multi-modal data and build flexible AI pipelines using SQL — all while providing best‑in‑class performance and cost efficiency.

Snowflake Marketplace Adds Agentic Products and AI-Ready Data from Leading News, Research, and Market Data Providers

 

Snowflake announced new agentic products on Snowflake Marketplace that accelerate agentic AI adoption across the enterprise. This includes Cortex Knowledge Extensions (generally available soon) on Snowflake Marketplace, which enables enterprises to enrich their AI apps and agents with proprietary unstructured data from third-party providers — all while allowing providers to protect their intellectual property and ensure proper attribution.  Users can tap into a selection of business articles and content from The Associated Press, which will help users further enhance the usefulness of results in their AI systems.

 

In addition, Snowflake unveiled sharing of Semantic Models (now in private preview), which allows users to easily integrate AI-ready structured data within their Snowflake Cortex AI apps and agents — both from internal teams or third-party providers like CARTO, CB Insights, Cotality™ powered by Bobsled, Deutsche Börse, IPinfo, and truestar.

 

Learn More:

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.
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 Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements.  As a result, you should not rely on any forward-looking statements as predictions of future events. 

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