Snowflake Summit 2025’s latest announcements made it clear: the path to genuine AI-driven impact hinges on frictionless access to data, the ability to act on it with clarity, and absolute confidence in its protection. The focus on making data interoperable, and enabling direct interaction with intelligence is about systematically dismantling the real-world obstacles that stand between data and business outcomes. This isn’t just about what Snowflake can do, but what your teams will do: faster, more accurately, and with greater certainty, to solve problems and build the future. Here’s a summary of some of the biggest announcements from Snowflake Summit 2025.
Enhanced Agentic AI Capabilities
Snowflake’s new Agentic AI capabilities enable business users and data scientists to turn structured and unstructured data into actionable insights, without complex tooling or infrastructure. This will absolutely change how analysts, particularly non-technical analysts, interact with data, using natural language to derive insights.
- Snowflake Intelligence (public preview is coming soon) offers a new agentic experience for securely conversing with data using natural language. Customers can not only find answers, but ask complex questions and take action, without writing code.
- Data Science Agent (private preview is coming soon) is an agentic companion that can boost productivity for data scientists by automating every step of ML workflows with natural language, including data prep, feature engineering and training.
- Cortex AISQL (in public preview) brings multimodal data processing using AI into familiar SQL syntax. Complex AI workflows are now more accessible by enabling teams to analyze unstructured data formats using SQL.
- AI observability in Snowflake Cortex AI (generally available soon) enables no-code monitoring of generative AI apps.
- SnowConvert AI is another great tool that helps translate legacy DB syntax into Snowflake syntax for quicker, seamless migrations. Having an interactive semantic layer to define key business logic and synonyms will also help to make the most of AI, rather than trying to get it to figure out the nuance of your business logic, which will often leave you frustrated.
Unlocking Data Interoperability
The longer it takes for data to move from source to action, the greater the risk to your competitive edge, and rigid systems only make that worse. Snowflake is trying to change that by giving data engineers the tools and platforms to navigate the modern data landscape with confidence. These include:
- Snowflake Openflow: a brand new open, extensible, managed multimodal data ingestion service designed to simplify data movement and integration. All data integration is in one platform, and hundreds of connectors and processors simplify data integration with a variety of data sources and strategic partners.
- dbt Projects on Snowflake: with this native option (public preview coming soon), data teams can build, run, and monitor dbt Projects directly in Snowsight UI, accelerating the development lifecycle of data pipelines, increasing productivity and providing some extra peace of mind.
Having a ”one stop shop” to figure out data ingestion will be extremely impactful (and may end up saving organizations money if they’re able to move away from third-party ingestion tools).
Moving Innovation Forward
Shifting from AI experimentation to delivering real business value lies in how well you can leverage not just your own data, but that of external parties in your ecosystem. That’s why Snowflake is aiming to make it easier to connect to and collaborate with AI-ready internal and external sources, extend agentic workflows, and build and deploy AI-driven apps while protecting private data.
- Cortex Knowledge Extensions (generally available soon): Enrich apps with real-time content from publishers like USA TODAY, The Associated Press, Packt, Stack Overflow and CB Insights while protecting intellectual property and supporting proper attribution.
- Sharing of Semantic Models (private preview): Allows users to integrate and share AI-ready internal data sets or third-party structured data from internal teams and third-party providers, and use natural language to “talk to data” from a variety of providers.
- Agentic Snowflake Native Apps on Snowflake Marketplace: A new way for providers to develop and offer Snowflake Native Apps that reference Cortex Agent APIs to automate tasks and interact with data, these interoperable agentic products can give data engineers, data scientists and others a fast track to deploying and creating value from agentic AI.
- Snowflake Native App Framework enhancements for security and interoperability: New features focused on application versioning, permissioning, app observability and compliance badging make it easy to build security into apps from the ground up.
Want to learn more about how Snowflake can help store your data securely, for deeper insights and impactful decision making? Reach out here.
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