Snowflake Unveils New Developer Tools to Supercharge Enterprise-Grade Agentic AI Development

No-Headquarters/BOZEMAN, Mont.--( BUSINESS WIRE)-- Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced a suite of new developer tools designed to help organizations rapidly build, test, and deploy cutting-edge, enterprise-ready AI apps faster and more securely. New enhancements to Snowflake’s developer collaboration environment, seamless open source integrations, and new data quality capabilities further accelerate productivity and reduce overhead, helping teams drive measurable business value at scale — all within a single, governed platform.

“The success of enterprise AI hinges on having the most trustworthy data, and the most productive developers,” said Christian Kleinerman, EVP of Product, Snowflake. “By delivering a single, intelligent, and governed environment, we're not just accelerating code development and execution – we're giving every developer a shorter, simpler path to build enterprise-ready AI apps that actually drive value. This is the new blueprint for enterprise innovation and a demonstration of how Snowflake is delivering on its promise of limitless interoperability."

“Snowflake’s new developer capabilities have been transformative, empowering us to build data pipelines with the flexibility and interoperability we need, all while using the tools that best fit our workflow,” said Andre Byfield, Principal Data Architect, Enlyte. “dbt Projects on Snowflake allowed us to deploy and orchestrate our dbt pipelines directly on the Snowflake platform rather than having to build out that cloud infrastructure ourselves. This represented real cost and time savings for our lean data engineering team and delivered real-world value to our stakeholders."

Build with AI for Accelerated Agentic AI Development

The era of agentic AI is already underway, with 20% of organizations actively deploying agents today and another 54% planning to deploy within the next 12 months 1. However, this exponential growth has only intensified the pressure on data engineering teams to rapidly manage the vast volumes and types of data that power AI.

Snowflake is addressing these pain points head-on by providing AI-native developer tools designed to help teams move into production faster, and with more confidence:

Snowflake Provides the Mission-Critical, Open Foundation for App Development

Snowflake empowers developers with world-class tooling, coupled with interoperability across a wide-range of third-party products, so they can build the way they want, with their preferred solution. This choice and flexibility is critical to developer productivity, allowing them to collaborate across AI app development and supercharge velocity.

With Snowflake’s latest innovations, developers can build using the tools they already know and love, without leaving the secure and governed Snowflake platform:

“As a non-profit that delivers life-saving care every day, every dollar counts. When we rebuilt our data and analytics platform, we needed right-size tooling that balances capability with simplicity and cost,” said Chris Androsoff, Director of Data, STARS. “The moment dbt became part of the Snowflake ecosystem, the path was clear. Today we experiment, codify, test, deploy, schedule, and monitor our entire dbt workflow natively inside Snowflake. Consolidating on one platform has created helpful simplicity, improved cost transparency, and freed our engineers to focus on delivering value faster.”

Snowflake Promotes Data Quality and Code Security to Build with Confidence

In order to deploy agentic AI apps at scale, data teams need to ensure that both the quality and security of the data feeding their initiatives is best-in-class. To simplify the complex task of monitoring and reporting on data reliability, Snowflake has enhanced its Data Quality User Experience (UI) (in public preview), allowing developers to assess how accurate and trustworthy the data is, and automatically generating a summary for increased insights. With upgrades to Code Security (now generally available), teams also benefit from new security constructs that remove the risk of unsecured access to developer code to eliminate data poisoning or block unauthorized model tampering.

Learn More:

1 MIT Technology Review Insights, Redefining Data Engineering in the Age of AI, October 2025. Based on a survey of 400 global senior data and technology executives.

2 "Apache Spark” is a registered trademark or trademark of the Apache Software Foundation in the United States and/or other countries.

3 Based on customer production use cases and proof-of-concept exercises comparing the speed and cost for Snowpark versus managed Spark services between November 2022 and May 2025. All findings summarize actual customer outcomes with real data and do not represent fabricated datasets used for benchmarks.

Forward Looking Statements

This press release contains express and implied forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, including statements regarding (i) Snowflake’s business strategy, plans, opportunities, or priorities (ii) the release, adoption, and use of Snowflake’s new or enhanced products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, (iv) Snowflake’s vision, strategy, and expected benefits relating to artificial intelligence and other emerging product areas, including the expected benefits and network effects of the AI Data Cloud, and (v) the integration, interoperability, and availability of Snowflake’s products, services, and technology offerings with and on third-party platforms. Other than statements of historical fact, all statements contained in this press release are forward-looking statements. 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. Forward-looking statements speak only as of the date the statements are made and are based on information available to Snowflake at the time those statements are made and/or Snowflake management's good faith belief as of that time with respect to future events. Except as required by law, Snowflake undertakes no obligation, and does not intend, to update these forward-looking statements to reflect events that occur or circumstances that exist after the date on which they were made.

© 2025 Snowflake Inc. All rights reserved. Snowflake, the Snowflake logo, and all other Snowflake product, feature and service names mentioned herein are registered trademarks or trademarks of Snowflake Inc. in the United States and other countries. All other brand names or logos mentioned or used herein are for identification purposes only and may be the trademarks of their respective holder(s). Snowflake may not be associated with, or be sponsored or endorsed by, any such holder(s).

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 12,000 customers around the globe, including hundreds of the world’s largest companies, use Snowflake’s AI Data Cloud to build, use and share data, applications and AI. With Snowflake, data and AI are transformative for everyone. Learn more at snowflake.com (NYSE: SNOW).