Snowflake Expands AI Data Cloud with New Agentic AI Capabilities and Developer Tools

Snowflake,  the AI Data Cloud company, has announced a wide range of new AI and data innovations designed to help organizations deploy agentic AI efficiently and securely. The new capabilities empower businesses to gain faster, more reliable insights by connecting all types of data—structured, unstructured, and semi-structured—within a unified, governed platform.

At the heart of these updates is the general availability of Snowflake Intelligence, an enterprise intelligence agent that enables employees to access and analyze complex information through natural language. The solution is built with enterprise-grade governance and security features, allowing organizations to maintain data confidentiality while democratizing analytics and AI-driven decision-making across departments. Over the past three months, more than 1,000 global enterprises, including Cisco, Toyota Motor Europe, and TS Imagine, have adopted Snowflake Intelligence to deploy over 15,000 AI agents for business operations. Powered by industry-leading AI models and a new Agent GPA framework that improves accuracy and error detection, Snowflake Intelligence enables companies to make decisions more confidently and efficiently.

Snowflake has also expanded its enterprise lakehouse capabilities through enhancements to Snowflake Horizon Catalog and Snowflake Openflow, now generally available. These updates give enterprises greater flexibility to unify data from multiple catalogs and platforms while maintaining governance and interoperability without vendor lock-in. New features such as open APIs from Apache Polaris and Apache Iceberg provide open access to data, while Interactive Tables and Warehouses (in private preview) enable near real-time insights. The upcoming real-time streaming analytics feature will allow organizations to act on live data within seconds, supporting use cases such as fraud detection, personalization, and IoT monitoring. Additional developments include a partnership with Oracle for real-time data streaming, the introduction of Snowflake Postgres and pg_lake for integrated database management, and new disaster recovery tools to improve data resilience.

To support developers, Snowflake has introduced a robust suite of AI-native tools that accelerate the creation and deployment of enterprise-grade AI applications. Cortex Code, currently in private preview, allows developers to interact with their Snowflake environment using natural language for query optimization and workflow management. Cortex AISQL, now generally available, enables the building of AI inference pipelines through simple SQL queries, while the forthcoming AI Redact feature will automatically detect and mask sensitive information from unstructured datasets. Developers can now use Workspaces, a centralized coding environment integrated with Git and VS Code, to collaborate and manage projects more efficiently. Additionally, dbt Projects on Snowflake allow for in-platform data transformation and monitoring, while Snowpark Connect for Apache Spark offers secure execution of Spark code directly on Snowflake’s engine.

Together, these innovations represent Snowflake’s next major step toward enterprise-scale AI adoption. By integrating intelligent automation, open data frameworks, and advanced developer tools, the company is creating a cohesive environment where AI can operate autonomously and securely. The expanded platform allows organizations to innovate faster, optimize workflows, and extract more value from their data—positioning Snowflake as a central player in the next phase of global AI transformation.