Snowflake expands agentic AI platform with business context and governance tools

SHARE UPDATED 09:00 EST / NOVEMBER 03 2026

Snowflake Inc. today announced a sweeping collection of artificial intelligence capabilities designed to bring business context, governance and autonomous development into the same environment, as enterprises increasingly hand over software engineering and everyday operations to AI agents.

The announcements, during the company’s Expedition 2026 virtual conference, include a new Business Ontology framework, expanded agent governance through Cortex AI Gateway, and autonomous data engineering capabilities that allow AI agents to build, monitor and troubleshoot data pipelines with less human intervention.

The company is betting that more coders and engineers will use AI throughout the software development lifecycle as creation moves even faster, while other back-end departments begin to adopt agents in their day-to-day work. For example, sales operations are creating agents that can analyze sales risks and prepare customer outreach without writing code.

“AI is industrializing software creation. Actually, it’s industrializing intelligence,” Chief Executive Sridhar Ramaswamy said. “What once took months can now take hours, days, or even minutes.”

Ramaswamy noted that while AI is changing the economics of software development, as agents take over tasks usually relegated to specialized developers, business users become developers. This is changing the competitive landscape, meaning that the advantage no longer goes to specialists, but to proprietary knowledge.

Snowflake is taking the field by helping ordinary AI models understand and contextualize that business knowledge. It does this with Business Ontology, an extension of its existing semantic views that lets organizations establish approved definitions used across the organization. Without a standard definition, two agents could respond to the same business-related question with incompatible answers, even when both agents have accurate underlying data.

Using information from Business Ontology, Snowflake CoCo, the coding agent for data teams, and Snowflake CoWork, the personal work agent for knowledge workers, use these approved business concepts to ground their responses.

This new feature is currently in private preview, but is headed to public preview soon.

Cortex AI Gateway arrives to become a single front door for agents within an organization. It is not entirely new; Snowflake introduced it in July 2026 as a centralized way to govern and monitor agents.

Today’s announcement expands its capabilities rather than introducing the gateway for the first time. The new updates include agent abuse detection, observability and tracing, Cortex sandboxes, AI cost governance, dynamic model routing and tools integration using technology from Snowflake’s Natoma acquisition.

“An agent that acts on your business has to be trusted, and it has to know three important things: what the data means, which data to trust, and what it’s allowed to do,” said Ramaswamy.

The platform most importantly applies existing security mechanisms, including data masking and access restrictions, to agent-driven operations while adding capabilities to monitor activity, detect potential abuse and maintain records of what agents do. The information technology and security teams can also apply cost controls, select models based on efficiency or accuracy and restrict which external tools agents can access granularly.

The underlying role of this governance, control and transparency is aligned with giving agents the same sort of role observation granted to employees. Treating them similarly in terms of autonomy.

Snowflake’s push comes amid a broader industry race to establish the control layer for enterprise AI agents. SAP has been expanding its Autonomous Enterprise architecture and governed Joule agents, while Salesforce has introduced its Enterprise AI Harness and AI Control Plane to secure autonomous workflows. Snowflake is approaching the same problem from the data platform side, seeking to become the foundation through which agents access trusted business information and operate under enterprise policies.

Snowflake also announced the public preview of Cortex Training, which will allow customers to tailor open-weight AI models with their own proprietary information.

The service is designed to make it simpler to create specialized models using post-training without needing vast arrays of graphics processing units. Snowflake lets them train models without managing the underlying infrastructure.

“Specialized, smaller models that come with more efficient responses, faster responses, and frequently cost benefits in terms of tokens,” Executive Vice President of Product Christian Kleinerman said.

Many enterprise companies will require sovereign control of their own AI models as increasing restrictions on foreign open-weight AI or regulations on handling sensitive information. It’s easier to audit what passes through an AI model on your own hardware than in a third-party vendor’s cloud.

Separately, Snowflake announced an expanded partnership with Oracle Corp. to make its platform available as a first-party service on Oracle Cloud Infrastructure. The integration will give customers easier access to Snowflake’s analytics and AI capabilities while allowing them to work directly through Oracle databases and applications.

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