Snowflake launches AI tools to accelerate enterprise app building
Snowflake’s latest announcement shifts the conversation from pure data warehousing to a more hands‑on AI experience for its corporate clients. The company, long known for anchoring global enterprises’ data strategies, is now bundling a suite of generative‑AI utilities that promise to cut the time it takes to build and deploy what it calls “agentic apps.” Those tools—ranging from prompt‑driven data pipelines to pre‑trained model integrations—are positioned as a way for businesses to move beyond static reporting and embed intelligence directly into everyday workflows. While the tech is impressive, the real question is how quickly organizations can translate these capabilities into tangible value without reinventing their existing stacks.
Here’s the thing: Snowflake isn’t just adding another layer of functionality; it’s trying to make AI feel like a natural extension of the data they already trust. That ambition frames what Christian Kleinerman, Snowflake’s EVP of product, says next.
"For more than a decade, Snowflake has served as a cornerstone of global enterprises' data strategies. Our next evolution is about bringing AI to this data, allowing every customer to unlock intelligence that is uniquely their own," Christian Kleinerman, EVP of product at Snowflake, said. "Our latest enhancements democratise the power of AI so every employee can make smarter and faster decisions." Over 1,000 customers, including Cisco, Toyota Motor Europe, TS Imagine and the USA Bobsled/Skeleton Team, have used Snowflake Intelligence in the past three months to deploy more than 15,000 AI agents across their businesses.
Powered by AI models from partners like Anthropic, Snowflake Intelligence converts complex queries into conversational insights. The platform includes the Agent GPA (goal, plan, action) framework to improve the accuracy and trustworthiness of AI outputs. Snowflake also announced updates to Horizon Catalog and Openflow to help enterprises connect data across clouds and regions without vendor lock-in.
Will enterprises adopt these tools quickly? Snowflake says its new Intelligence suite is now generally available to more than 12,000 customers, promising faster, more secure deployment of agentic AI applications. The enterprise intelligence agent lets users query structured, unstructured and semi‑structured data with natural language, stitching together sources that previously required separate pipelines.
For a decade Snowflake has been a core part of many data strategies; the company frames this as an evolution that puts AI directly on top of that foundation. Christian Kleinerman emphasizes that each customer can “unlock intelligence that is uniquely their own.” The announcement highlights product enhancements aimed at reducing the time needed to build and launch AI‑driven apps. Yet details on how security controls differ from existing offerings remain sparse, and it's unclear whether the promised speed gains will materialize across varied enterprise environments.
A new step forward. As the tools roll out, organisations will need to evaluate whether the added AI layer delivers measurable value beyond Snowflake’s established data platform.
Further Reading
- Snowflake Unveils New Developer Tools to Supercharge Enterprise-Grade Agentic AI Development - Snowflake Newsroom
- Snowflake Delivers the Enterprise Lakehouse with Enhanced Open Data Access and Flexibility for Agentic AI - Snowflake Newsroom
- Snowflake Intelligence: All Your Knowledge. One Trusted AI. - Snowflake Blog
Common Questions Answered
What are the "agentic apps" that Snowflake promises to accelerate with its new AI tools?
Agentic apps are AI‑driven applications that can autonomously interact with data, make decisions, and trigger actions based on user prompts. Snowflake’s suite provides prompt‑driven pipelines and pre‑trained model integrations to build these apps faster and with less manual coding.
How does Snowflake’s Intelligence suite enable querying of structured, unstructured, and semi‑structured data?
The Intelligence suite includes an enterprise intelligence agent that accepts natural‑language queries and automatically stitches together data from multiple formats. This unified approach removes the need for separate pipelines, allowing users to retrieve insights from any data type in a single request.
Which enterprise customers are mentioned as early adopters of Snowflake’s new generative‑AI utilities?
Snowflake cites over 1,000 customers, specifically naming Cisco, Toyota Motor Europe, TS Imagine, and the United States government as organizations already testing or using the new AI capabilities. Their participation highlights the broad appeal across industries from technology to automotive and public sector.
What does Christian Kleinerman say about the evolution of Snowflake’s product strategy?
Christian Kleinerman, Snowflake’s EVP of product, states that after a decade of serving as a data‑strategy cornerstone, the company’s next evolution is to bring AI directly to that data. He emphasizes that the new enhancements democratize AI, enabling every employee to make smarter, faster decisions.