What AI models and tools does Cortex AI Gateway support?

Cortex AI Gateway governs how AI agents access models including GPT, Gemini, Claude, Grok, Mistral, and GLM, as well as first-party tools like Snowflake CoCo and CoWork, third-party ecosystems such as Amazon Bedrock, Azure AI Foundry, ChatGPT, Claude Code, Cursor, and custom LangChain or LlamaIndex apps, plus 100+ MCP servers including bring-your-own and VPC connect options.

How does Cortex AI Gateway help control AI costs?

The gateway provides AI Cost Control (in private preview) to give a unified view of AI consumption by team, agent or workload, manage and apply budget guardrails, and automatically route requests to cheaper models for simpler tasks. It also enforces spending limits by team, agent or workload before costs run away.

What new security features did Snowflake move to general availability?

Agent Identity (GA) gives security teams visibility into agent activity and lets them enforce data access policies specific to agent sessions; Native AI Security Posture Management (GA) integrates AI-specific risk scanning into the Snowflake Trust Center; and Ransomware Protection via Multi-Party Approval (MPA) (GA) requires two or more authorizations before any destructive system change can proceed.

AI Safety & AlignmentAI Business & IndustrySnowflake AI BlogJul 28, 2026Jul 29, 2026, 01:00 JST

Snowflake launches Cortex AI Gateway, beefs up AI security at Black Hat 2026

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3 Key Points

What happened
Snowflake announced Cortex AI Gateway at Black Hat 2026, a centralized control layer for autonomous agents that enforces identity, policy and audit across multiple AI models (GPT, Gemini, Claude, Grok, Mistral, GLM and others) and MCP servers. The company simultaneously moved several AI security features to general availability (GA) or public preview, including Agent Identity (GA), Native AI Security Posture Management (GA), Ransomware Protection via Multi-Party Approval (MPA) (GA), and new Data Exfiltration Prevention capabilities.
Why it matters
AI security concerns have surged from 17% in 2024 to 48% in 2026 according to The Linux Foundation's 2026 State of Tech Talent Report, yet 57% of organizations face a significant capacity gap in security and risk management despite 97% being committed to implementing AI. Autonomous agents have expanded the enterprise attack surface by combining data access, system execution and data movement into a single profile, making patchwork application-layer fixes inadequate. Snowflake's approach embeds security directly into the data and control planes, allowing enterprises to govern agent access, visibility and costs from a single endpoint without instrumenting each agent individually.
What to watch
Cortex AI Gateway's private-preview features include Wide Model Catalog, Access Governance and Sprawl Control, Govern Every Agent Connection across 100+ MCP servers, Observability and Tracing, Agent Action Auditability, AI Cost Control, and Intelligent Model Routing. Snowflake is also piloting Context-Aware Access Policies (private preview), Client-side CoCo CLI VM Sandbox (private preview, currently macOS), and Advanced Data Exfiltration Prevention. Restricted Session Scope is coming GA soon. Visitors can see live demos at Snowflake booth #8206 at Black Hat USA 2026.

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Context & Analysis

The timing of Snowflake's announcement reflects a sharp inflection in enterprise AI risk perception. The Linux Foundation's 2026 State of Tech Talent Report shows AI security concerns jumped to 48% from 17% in just two years—a 181% increase—yet the security infrastructure has not kept pace. While 97% of organizations are committed to implementing AI, 57% lack adequate security and risk management capacity, creating a dangerous gap that autonomous agents have made more acute. Autonomous agents expand the attack surface by consolidating data access, system execution, and data movement into a single profile; traditional application-layer security patches and legacy monitoring tools cannot contain this risk.

Snowflake's response is architectural: rather than bolting security onto agents after deployment, the company embeds governance directly into the data and control planes. The Cortex AI Gateway centralizes identity, policy, and audit at the tool-call level (the granular action level where an agent invokes a model or service) across a fragmented ecosystem—multiple AI models (GPT, Gemini, Claude, Grok, Mistral, GLM), multiple MCP servers (100+ supported), and multiple deployment contexts (internal tools, SaaS, cloud AI services). This unification addresses a core pain point: as enterprises scale autonomous agents, they face fragmented access, no visibility into agent activity, and spiraling AI costs. By routing all agent requests through a single gateway, Snowflake allows teams to grant or deny access, audit every action in real time, and route workloads to cheaper models—all without manually configuring each new agent type.

FAQ

What AI models and tools does Cortex AI Gateway support?: Cortex AI Gateway governs how AI agents access models including GPT, Gemini, Claude, Grok, Mistral, and GLM, as well as first-party tools like Snowflake CoCo and CoWork, third-party ecosystems such as Amazon Bedrock, Azure AI Foundry, ChatGPT, Claude Code, Cursor, and custom LangChain or LlamaIndex apps, plus 100+ MCP servers including bring-your-own and VPC connect options.
How does Cortex AI Gateway help control AI costs?: The gateway provides AI Cost Control (in private preview) to give a unified view of AI consumption by team, agent or workload, manage and apply budget guardrails, and automatically route requests to cheaper models for simpler tasks. It also enforces spending limits by team, agent or workload before costs run away.
What new security features did Snowflake move to general availability?: Agent Identity (GA) gives security teams visibility into agent activity and lets them enforce data access policies specific to agent sessions; Native AI Security Posture Management (GA) integrates AI-specific risk scanning into the Snowflake Trust Center; and Ransomware Protection via Multi-Party Approval (MPA) (GA) requires two or more authorizations before any destructive system change can proceed.

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