Snowflake Intelligence (public preview soon) offers business users and data professionals a unified conversational experience — powered by intelligent data agents — to ask natural language questions and instantly uncover actionable insights from both structured tables and unstructured documents. Snowflake is also unveiling Data Science Agent (private preview soon), an agentic companion that boosts data scientists’ productivity by automating routine ML model development tasks. These innovations enable users to simplify their AI and ML workflows, democratize access to data across their businesses, and eliminate the technical overhead that slows down business decision-making — all through natural language interactions within Snowflake.

“AI agents are a major leap from traditional automation or chatbots, but in order to deploy them at scale, businesses need an AI-ready information ecosystem. This means enterprises must be able to unite data silos, maintain enterprise-grade security and compliance, and have easy ways to adopt and build agents," said Baris Gultekin, Head of AI, Snowflake. "Snowflake Intelligence breaks down these barriers by democratizing the ability to extract meaningful intelligence from an organization’s entire enterprise data estate — structured and unstructured data alike. This isn't just about accessing data, it's about empowering every employee to make faster, smarter decisions with all of their business context at their fingertips."

Today, organizations are plagued by inefficient decision-making due to disjointed data governance, silos between data formats, and a shortage of technical data analysts who can code and synthesize information across the business. Snowflake Intelligence eliminates these operational challenges, allowing non-technical users and business teams to have conversations with their enterprise data in natural language — all without writing a single line of code.