Google is building Gemini Enterprise Agent Platform as a shared control layer for enterprise AI agents. Agent identity, a registry of approved agents and tools, default-deny access policies, content filtering and a network gateway all sit inside one Google Cloud product family. That makes the word “gatekeeper” defensible as a description of where Google is placing governance: at the layer that decides which agents exist, what they can reach and who may run them. It does not show that Google intends to shut out competitors, or that it already dominates enterprise agents. The sections below separate what Google has announced from what it has only claimed.
What Google announced, and when
On April 22, 2026, Google Cloud launched Gemini Enterprise Agent Platform and described it as the evolution of Vertex AI. According to the announcement, the platform combines model selection, model building and agent building with agent integration, DevOps, orchestration and security. Google’s product documentation describes it as covering the full AI lifecycle, from model access through deploying and managing agents.
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The most consequential sentence in that launch concerns delivery rather than branding. Google Cloud wrote:
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Is Google replacing Vertex AI?
Google positions Agent Platform as the path forward for Vertex AI, and says new Vertex AI services and roadmap changes will arrive only through it. That is a statement about where future development ships. It is not a complete migration plan: the announcement does not spell out how existing standalone Vertex AI workloads move over, or on what timeline. Teams running production Vertex AI deployments should check Google’s current product documentation before assuming any change to their own setup.
Two products with two jobs
Much of the confusion around the name comes from two layers that Google presents as one stack. Gemini Enterprise is the employee-facing application. Gemini Enterprise Agent Platform is the developer and governance layer beneath it. Google’s October 9, 2025 Gemini Enterprise launch framed the app as a single front door for workplace AI. The April 2026 platform launch described that app as built on Agent Platform, with governance, security and identity capabilities included.
| Aspect | Gemini Enterprise | Gemini Enterprise Agent Platform |
|---|---|---|
| Primary users | Employees | Developers and the teams that govern agents |
| Role | Front door to discover, create, share and run agents | Build, scale, govern and optimize agents |
| Named components | Connections to Google Workspace, Microsoft 365, Salesforce and SAP; governance to visualize, secure and audit agents; Agent Gallery | Agent Studio (low-code), Agent Development Kit (code-based and model-agnostic), Model Garden, runtime, memory, RAG and vector search, Agent Identity, Agent Registry, Agent Gateway |
| Primary Google source | Gemini Enterprise launch, October 9, 2025; platform launch, April 22, 2026 | Platform launch, April 22, 2026, and Google Cloud product documentation |
The October 2025 pitch for the front door rests on data access. Google said:
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“An agent is only as good as its context, so Gemini Enterprise securely connects to your company’s data wherever it lives — from Google Workspace and Microsoft 365 to business applications like Salesforce and SAP.”
That matters for the gatekeeper question. Whoever mediates how employees find, launch and feed data to agents holds a position in the workflow, not only in the model layer.
Can Google control which agents access company data?
Within the platform, yes, and Google’s governance documentation names specific mechanisms. Each covers a different point in the path from agent to data, and none does anything unless it is configured for the agents in question.
Agent Identity
Agent Identity gives an agent a secure identity, which Google describes as a SPIFFE ID. SPIFFE is an open standard for workload identity. Google says the identity is used for authentication, access control and auditing, so access decisions and audit records refer to a specific agent.
Agent Registry and approved destinations
Agent Registry catalogs approved agents, tools, MCP servers and endpoints. Agent Gateway consults this registry when it checks permissions, which makes the registry the reference list for what an agent may reach. Its effect therefore depends on what an organization has registered.
Default-deny access through IAM
Google documents default-deny behavior: a connection is refused unless an explicit IAM policy grants access. This is the core of the gatekeeper model. Access is written as an allow-list in IAM, rather than a permissive default that teams must lock down themselves.
Model Armor content controls
Model Armor scans prompts and tool responses. Google says it is designed to block prompt injection, leaks of sensitive data and harmful content. It inspects content, not identity or destination, so it complements the other controls rather than replacing them.
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Semantic policies
Semantic policies are written in plain language and restrict how agents use tools, including blocking unsafe combinations of tools. They are easier for non-engineers to review than permission lists. The material available does not describe how a plain-language policy is translated into enforcement, so test these policies against your own sensitive tools before relying on them.
What Agent Gateway actually controls
Agent Gateway governs agent communications and is where network enforcement lives. It checks permissions against Agent Registry and can enforce VPC Service Controls perimeters for agent traffic. Its scope is narrower than “central control” suggests, and Google’s documentation spells out the limits.
The first limit is direction. Google documents two modes, and they are not supported equally by every runtime:
| Runtime | Client-to-Agent ingress | Agent-to-Anywhere egress |
|---|---|---|
| Agent Runtime | Supported | Supported |
| Gemini Enterprise | Not supported | Supported (the only mode it supports) |
- Capacity: one gateway instance can govern up to 5,000 resources registered in Agent Registry, according to Google Cloud documentation as accessed on October 9, 2026.
- Certificates: for certain private-CA trust configurations, the documentation lists manual PEM rotation as a limitation, so certificate renewal is an operational task you own.
- Coverage: not all agent communication automatically passes through the gateway. Which traffic is governed depends on deployment and runtime mode, so confirm both before assuming a flow is covered.
Does Gemini Enterprise work with non-Google models and tools?
Yes, with a qualification about what “open” means here. Google’s Model Garden includes Google, third-party and open models. Google’s April 2026 announcement says Model Garden provides access to more than 200 models. That is a vendor-reported catalog count, not an independent comparison of model quality or coverage.
The tooling is open in a second sense. The Agent Development Kit is code-based and model-agnostic, Google says the platform supports the open-source ADK and other open-source frameworks, and Google documents MCP and A2A interoperability. Agent Studio is the low-code option for building agents without that code layer.
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Interoperability is not the same as portability of governance. The material available does not establish how far identity assignments, registry entries, IAM policies and semantic policies would carry over if an agent ran outside Google’s managed services. Plan for that gap if portability matters to your architecture.
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What the evidence supports
Three things are documented rather than inferred. First, Google is consolidating development, runtime, identity, registry, policy and observability under one product family, and says future Vertex AI work ships only through it. Second, governance sits at a common layer: identity, approved destinations, default-deny access, content controls and network enforcement all route through Google-managed services. Third, the employee front door and the developer platform are designed to share that layer.
That is a control-plane strategy: Google is positioning itself as the place where enterprise agents are approved, governed and distributed. In that narrow sense, “gatekeeper” is an accurate word. It describes the governance and distribution layer, not ownership of every model or agent that runs on it.
What it does not establish
- Market position. The available material contains no market-share data and no evidence that Google dominates enterprise agents.
- Intent to exclude rivals. Google’s statements about third-party models, open frameworks, MCP and A2A cut against an exclusion reading, but they are Google’s own claims, not independent findings.
- Customer outcomes. The partner and developer figures discussed below are Google-reported counts or program goals, not measured results.
- A competitor comparison. Any comparison with rival platforms has to answer the same questions for each one: identity and authorization, registry and approved-tool controls, policy and prompt-security enforcement, model and framework portability, gateway modes, auditability and evaluation, integration with enterprise data and identity systems, and commercial and regional availability. This article answers those questions only for Google.
- Current availability. Google describes this as an evolving product. Regional availability, general-availability status of each component, pricing and commercial terms are not established by the material available, and component names and scope may change.
Partners and the marketplace channel
The ecosystem is the other half of the gatekeeper argument, because whoever distributes agents and implementation services gains leverage over how they are adopted. Google’s October 2025 Gemini Enterprise announcement named consulting and services firms in two groups. These are Google’s statements about its own ecosystem, not independent evaluations or endorsements.
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|---|---|
| BCG | Planning, deployment and custom agent development |
| Capgemini | Planning, deployment and custom agent development |
| HCLTech | Planning, deployment and custom agent development |
| Infosys | Planning, deployment and custom agent development |
| McKinsey | Planning, deployment and custom agent development |
| TCS | Planning, deployment and custom agent development |
| Wipro | Planning, deployment and custom agent development |
| Accenture | Internal adoption and expanded services |
| Cognizant | Internal adoption and expanded services |
| Deloitte | Internal adoption and expanded services |
| KPMG | Internal adoption and expanded services |
| PwC | Internal adoption and expanded services |
- Ecosystem size: Google reports more than 100,000 partners in its October 2025 announcement. That is a broad ecosystem figure, not a count of agent vendors.
- Agent discovery: Google says its agent finder lets customers discover thousands of agents reviewed for security and interoperability.
- Marketplace channel: in April 2026, Google said Google Cloud Marketplace agents are surfaced inside Gemini Enterprise’s Agent Gallery, and that Google validates gallery agents against its requirements for security and interoperability.
- Developer goal: Google’s GEAR educational sprint is designed to empower one million developers to build and deploy agents. This is a stated program goal, not a measured outcome.
Google also says partners can market agents and earn revenue from them. The material available does not establish referral commissions, affiliate eligibility or program terms for these partners, so treat any revenue-share claim as unverified until you check Google’s partner program terms directly.
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