Snowflake announced Cortex AI Gateway on Tuesday, a centralized control layer designed to govern how AI agents — including those built by competitors like Anthropic's Claude Code and Cursor — access enterprise data, tools, and models. Alongside the gateway, the company unveiled a first wave of security integrations with 1Password, Aembit, Linx Security, SailPoint, and Saviynt, an unusual coalition of identity vendors who often compete with one another, now aligned around a shared trust model for autonomous agents. The announcement, made from the company's no-headquarters base in Bozeman, Montana, is Snowflake's most aggressive move yet to position itself not merely as the place where enterprise data lives, but as the control plane that decides what AI agents are allowed to do with it. "The next era of AI won't be built through more walled gardens. It will be built through secure agent interoperability," Mayank Upadhyay, Snowflake's chief security and trust officer, told VentureBeat in an exclusive interview. "If every vendor builds a closed ecosystem of agents, enterprises simply recreate the fragmentation they've spent years trying to solve. Instead of breaking down silos, they create a new generation of AI silos that limit innovation and make it harder to scale AI across the business." Why decades-old enterprise security models break when AI agents become the actors The core argument animating today’s announcement is that decades of enterprise security architecture rests on an assumption that no longer holds — that the actor behind every access request is a person. "Traditional security was built for a world where humans were the actors. AI agents change that completely. For decades, security models assumed people would access one application at a time, operating at human speed and within relatively defined boundaries," Upadhyay said. The deeper issue, he argued, is not novelty but exposure: "The challenge isn't that AI creates entirely new security problems. It's that AI exposes the blind spots we've always had." Organizations have never had perfect visibility into every API, dataset, and workflow, Upadhyay noted, and at human speed those gaps were manageable. Agents operating at machine speed can "combine access across systems and act on permissions that were never intended to be exercised together, amplifying those longstanding risks." His conclusion: "In the agentic era, trust can't be a one-time decision made at login. It has to be continuously verified through every agent, every action, and every interaction across the enterprise." Nancy Wang, chief technology officer of 1Password, described the failure mode in more visceral terms. When agents first arrived, she told VentureBeat, the default pattern was dangerously simple: "Let me just give the agent my credentials and it can just act as me… let's imagine you're the head of security or the head of IT, and you have access, especially admin access, to all of the systems. Well, now suddenly your agent now has admin access to all of the systems, and so it could exfil data… if it's subject to a prompt injection, for example." The audit trail becomes equally useless, she added: "Imagine the audit logs show that Michael sent a couple million dollars to an offshore account… It raises eyebrows when, in fact, it could just be an agent going off the rails and doing things that you never authorized." Her prescription, and the premise of 1Password's integration with Snowflake, is blunt: "Agents need their own identity." Inside Cortex AI Gateway: how Snowflake plans to govern agent access and rein in runaway AI costs Cortex AI Gateway, which will enter public preview soon, functions as a connective layer for what Snowflake calls "all trusted agent activity." It governs both first-party agents built inside Snowflake, such as Snowflake CoWork and CoCo, and third-party agents built on external platforms. With support for more than 100 MCP servers — the Model Context Protocol connectors that have become the de facto standard for wiring agents to enterprise tools — the gateway centralizes access policies, authentication, permissions, and audit logging in a single place. The gateway also addresses a less glamorous but increasingly urgent problem: runaway AI spending. It gives IT and finance teams a unified view of AI consumption, attributes costs to the specific teams, agents, or workloads driving them, and enforces spending limits before bills spiral. Upadhyay described how those costs compound in practice. "AI is dynamic. Agents can invoke multiple models, call different tools, and execute multi-step workflows, creating consumption patterns that can change from one task to the next. For example, an enterprise may deploy an AI assistant to help employees answer internal questions. A simple request that only requires retrieving a document could unintentionally be routed through a more expensive reasoning model, trigger additional searches across multiple systems, or invoke unnecessary workflows." At scale, with thousands of employees and hundreds of agents, small inefficiencies become significant line items. The gateway builds directly on Snowflake's May 2026 acquisition of Natoma, a 27-person startup whose centralized MCP gateway enforced identity, policy, and audit at the tool-call level. Forbes reported at the time that the deal — announced the same day as Snowflake's $1.33 billion quarterly product revenue report and a $6 billion AWS compute commitment — was the smallest of the day's three announcements by dollar value but the most revealing about where Snowflake believes the next platform fight sits: not in the data warehouse, but in the layer that decides what an agent may touch and records what it did. Dual attribution and task-scoped access: the technical blueprint for trusting autonomous agents The technical centerpiece of the partner integrations is what Snowflake calls dual attribution. "By logging both the verified non-human identity of the agent and the specific human who authorized the task, we ensure task-scoped access and complete auditability for every action taken across the enterprise," Upadhyay said. That answers a question that has stumped security teams: when an agent takes an action, whose action is it? The Snowflake model says the answer is both — the agent's, and the human's who delegated the task — and both

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