Snowflake launches AI control tools for business definitions

Snowflake has introduced Business Ontology and Cortex AI Gateway for AI agents, aimed at giving enterprises more control over how agents use business definitions, data access and spending.

The tools are intended to address a problem many businesses face as they deploy AI agents across different systems, clouds and data platforms. Snowflake cited research it sponsored with MIT Technology Review Insights, which found that 55% of executives saw a lack of business context as the main cause of poor-quality AI agent insights, while 45% pointed to fragmented or inaccessible data.

Business Ontology, part of Snowflake Horizon Catalog, is designed to give organisations a single governed source for official business definitions. This is intended to help agents return answers based on approved meanings for terms such as net revenue, rather than conflicting interpretations drawn from separate dashboards, analysts or data dictionaries.

The feature links those definitions to the tables and views that implement them across data held inside and outside Snowflake. Every change is logged, creating an audit trail that shows what a term meant at a given time and who approved it.

Snowflake said the product works alongside Semantic View, which handles how a term is calculated, and Cortex Sense, which infers operational knowledge that has not been formally documented. Together, these elements create a shared business context for agents, applications and staff.

Christian Kleinerman, Executive Vice President of Product at Snowflake, set out the company's position on governance in AI deployments.

"For decades, governance gave organizations the confidence to make decisions with correctness, security and compliance. In the agentic era, governance is no different: it promotes trust and accelerates AI adoption. The enterprises that win won't be the ones with the most agents. They'll be the ones whose agents know exactly what the business means, access the right data, abide by specified governance and guardrails, and can account for actions taken. By extending Snowflake Horizon Catalog with Business Ontology and Cortex AI Gateway, context and governance stop being afterthoughts and become the foundation every agent is built on for the agentic enterprise," Kleinerman said.

Shared definitions

Some early users said the appeal lies in replacing static dictionaries with centrally maintained definitions that AI systems can use directly.

"The value of a data product depends on everyone agreeing what each attribute means, whether it's a household income band or a B2B firmographic segment. As agents become how people query that data, those definitions can't live in a static data dictionary. Business Ontology gives every definition an accountable owner, links it to the data that implements it, and makes it the answer every agent returns. As early product adopters, this is what lets us put agents in front of our data with confidence," said Joe Tobey, Head of Data Product Engineering at dentsu.

Merkle, part of dentsu, also highlighted the issue of inconsistent meaning across complex data environments.

"Semantic drift is one of the most underestimated risks in multi-partner data environments - and at Merkle, dentsu's data and technology agency, we operate inside some of the most complex ones in the industry. Snowflake's Business Ontology closes that gap at the infrastructure level, giving every definition an owner and every downstream system a single governed answer. That's what makes the clean room and RMN architectures we build at Merkle, on Snowflake, reliable enough to act on," said Morten Lileng, Global Head of Engineering at dentsu.

Control layer

Cortex AI Gateway is also part of Horizon Catalog and is positioned as a central control point for agents. Snowflake said it applies a single set of policies to connections across different clouds, frameworks and AI providers, while extending existing security and governance rules to autonomous software agents.

The gateway includes controls for model and tool access, records of agent activity, cost attribution and spending limits. It also includes monitoring intended to detect misuse, such as agents operating beyond permissions or employees attempting to use them to bypass approvals or extract sensitive data.

Snowflake said traces of what each agent did are recorded in the customer's own Snowflake account, allowing teams to examine which models were called, which tools were used and what each task cost. It added that model routing can direct requests to approved models based on cost, accuracy and latency requirements.

According to Snowflake, customers using the gateway include Glean and Kargo, while Uniphore is extending the controls to customers using its own orchestration platform.

"Enterprise AI needs more than access to data. It needs an understanding of how people, information and workflows connect across the business. At Glean, we bring that context together across enterprise systems to make AI agents more intelligent and effective. As agents become more sophisticated and operate across more systems, that context must be matched with equally strong governance. Snowflake's Cortex AI Gateway helps us extend visibility and control across AI interactions, supporting our ability to scale AI securely and responsibly," said Emrecan Dogan, Chief Product Officer at Glean.

Kargo focused on the product's cost management element.

"We run a lot of AI against a lot of data, and the question we couldn't answer was which teams and which agents were driving the spend. Cortex AI Gateway gave us that breakdown, plus hard limits so a runaway process doesn't quietly burn through a budget. Routing each request to the right model means our routine work isn't running on our most expensive one. We're running more agents than ever and we know what each of them costs," said Andy Owens, Vice President of Data and AI at Kargo.

"Enterprises don't just need more agents. They need to industrialize AI across the business. Snowflake gives our joint customers a governed data foundation. Uniphore's zero-copy Data & AI Orchestration Platform gives customers the ability to autonomously create the data ontology, fine-tune SLMs and build agents while data stays in place, and governance carries through to every agent we deploy. Cortex AI Gateway keeps that model choice accountable as customers scale from a handful of use cases to dozens," said Frank Petterson, Chief Product and Technology Officer at Uniphore.