Gemini Enterprise Agent Platform is Google Cloud's enterprise agent platform for building, orchestrating and governing AI agents that work across a company's data, apps and browsers, aimed at IT, data and platform teams at mid-size to large organizations rather than individual consumers.
Who it's for
The platform targets enterprises already invested in Google Cloud or Google Workspace that want a central hub for agents rather than a single point solution — think IT operations, knowledge management, and business-process teams building or deploying agents for search, research, coding assistance or task automation across the company. It is less suited to solo developers or small teams wanting a lightweight, cheap agent builder, since it is priced and packaged as a per-seat enterprise product.
How it works
Agents are assembled from an agent gallery or built custom, then connected to enterprise systems and data sources, with event-based triggers so an agent can react when something changes rather than only running on demand. The platform supports multi-agent orchestration, letting several specialized agents collaborate on a larger task, and includes agents capable of browser and computer use — navigating web interfaces and internal tools the way a person would. Rather than locking teams into a single model, it offers multi-model choice, so agents can call Gemini or other supported models depending on the task, and every agent action is captured for governance through built-in audit logging.
Pricing
Gemini Enterprise Agent Platform is billed per seat, with plans starting from roughly $30 per user per month. Actual cost depends on the tier and the volume of agent usage across your organization, and Google periodically adjusts its enterprise AI pricing, so confirm current tiers on Google Cloud's pricing page before budgeting.
Strengths and trade-offs
The platform's strengths are deep enterprise connectivity, multi-agent orchestration, model flexibility, and browser/computer-use agents that can operate existing web tools without custom integrations — all backed by Google Cloud's infrastructure and audit logging for governance. The trade-offs are that it is a fully managed cloud product with no self-hosted option, per-seat pricing can get expensive at scale, and because it's a fast-moving, recently rebranded product (formerly Agentspace), documentation and feature scope are still evolving, so it's worth validating specific connectors and compliance details directly with Google before a large rollout. For organizations already standardized on Google Cloud, it's a natural place to consolidate agent development; others should weigh it against platform-neutral alternatives. In practice, this means an IT team can stand up a research agent, a coding-assistant agent and a customer-facing agent from the same underlying platform, sharing connectors and audit trails rather than maintaining separate infrastructure for each use case.