Central AI platform teams
Offer developers a governed path from experimentation to production while standardizing identity, deployment, monitoring, and policy.
Independent tool overview
Gemini Enterprise Agent Platform at a glance
Gemini Enterprise Agent Platform is Google Cloud's developer platform for building, deploying, governing, and improving production AI agents. It is the evolution of Vertex AI and combines more than 200 models with low-code and code-first development, managed runtime, memory, security, and observability.
Visit the official Gemini Enterprise Agent Platform site ↗
- Best for
- Enterprises building and governing production agent fleets on Google Cloud
- Former foundation
- Evolution of Vertex AI, with future services and roadmap delivered through Agent Platform
- Model choice
- 200+ first-party, open, and third-party models through Model Garden
- Build options
- Low-code Agent Studio and code-first Agent Development Kit
- Pricing
- Usage-based Google Cloud pricing; new customers may receive $300 in credits
Overview
What Gemini Enterprise Agent Platform is
Gemini Enterprise Agent Platform is the technical foundation beneath Google's broader Gemini Enterprise portfolio. Developers and platform teams use it to create agents for products and internal operations, while the separate Gemini Enterprise app gives employees a governed place to discover and run those agents.
Google positions Agent Platform as the evolution of Vertex AI: existing model selection, training, tuning, and ML services now sit alongside Agent Studio, Agent Development Kit, long-running runtime, Memory Bank, agent identity, registry, gateway, simulation, evaluation, and observability.
This is a cloud platform rather than a fixed-price SaaS tool. Real cost includes model tokens, runtime compute and memory, stored sessions and memories, tools, grounding, networking, data services, observability, and any committed throughput.
Use cases
Who Gemini Enterprise Agent Platform is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Regulated enterprises
Track agents, permissions, tools, models, and execution through centralized registry, gateway, identity, audit, and evaluation controls.
Google Cloud data estates
Build agents close to BigQuery, databases, Google Workspace, security services, and existing Google Cloud infrastructure.
Multi-model development
Choose among Gemini, Gemma, media models, and supported third-party models while keeping a common development and governance layer.
Capabilities
Core Gemini Enterprise Agent Platform features
Agent Studio and ADK
Build visually in a low-code studio or define sophisticated multi-agent logic with the open-source Agent Development Kit.
Model Garden
Access more than 200 Google, open, and third-party models, including supported Anthropic models, then tune or route by workload.
Agent Runtime and Memory Bank
Deploy managed agents that can maintain state, run for extended periods, and use persistent context across sessions.
Agent Identity
Assign an agent a distinct identity so access can follow least-privilege policies and actions have clear ownership and auditability.
Agent Registry
Catalog approved agents, MCP servers, and connections so teams can reuse sanctioned capabilities and administrators can manage sprawl.
Agent Gateway
Centralize network policy, tool access, security guardrails, and monitoring for agents acting across internal and external systems.
Simulation, evaluation, and observability
Test against synthetic users and virtual tools, score live behavior, trace reasoning and tool use, detect drift, and debug failures.
Open protocols and remote MCP
Use ADK, A2A, MCP, and a managed remote MCP server to connect Google Cloud resources with internal or external agent tooling.
Process
How the Gemini Enterprise Agent Platform workflow works
Step 1
Define the business outcome and risk
Specify the workflow, allowed decisions, sensitive data, failure modes, approval points, latency target, and measurable success criteria.
Step 2
Choose the build path and models
Prototype in Agent Studio or ADK, select the least expensive model that meets quality needs, and design explicit tool and data contracts.
Step 3
Test before deployment
Use simulations, adversarial cases, deterministic tests, rubric-based evaluation, and human review for high-impact actions.
Step 4
Deploy with identity and guardrails
Give each agent a clear owner and least-privilege identity, register approved capabilities, route tool traffic through policy controls, and require approvals where needed.
Step 5
Monitor quality, security, and cost
Trace executions, score live outcomes, detect drift, review incidents, measure token and infrastructure cost, and continuously refine the agent.
Cost
Gemini Enterprise Agent Platform pricing and free plan
Agent Platform is usage-based. Google Cloud bills the models, compute, memory, storage, sessions, tools, grounding, networking, and supporting services an implementation consumes. Model rates vary by model, context length, region, consumption option, and commitment.
New customer proof of concept
Up to $300 in Google Cloud credits
For evaluating Agent Platform and other eligible Google Cloud services.
- Requires a Google Cloud billing account
- Credits are shared with eligible Google Cloud usage
- Usage beyond credits is billed by resource
Pay-as-you-go
Usage based
Default choice for prototypes and variable production traffic.
- Gemini 3.7 Flash promotional global rate through December 31, 2026: $0.75 per 1M input tokens and $3.75 per 1M output tokens
- Gemini 3.7 Flash standard rate from January 1, 2027: $1.50 input and $7.50 output per 1M tokens
- Gemini 3.1 Pro Preview for inputs up to 200K tokens: $2 input and $12 output per 1M tokens
- Non-global regions and long-context requests can cost more
- Agent infrastructure and connected Google Cloud services are billed separately
Alternative consumption modes
Varies
Balance cost, latency, reliability, and throughput for production workloads.
- Priority processing for higher reliability
- Flex and batch for latency-tolerant discounted work
- Provisioned Throughput for committed capacity and predictable service
- Flexible Savings Plans for eligible committed spend
Enterprise architecture and quote
Custom
For large deployments requiring capacity planning, commercial terms, support, and implementation help.
- Use the Google Cloud pricing calculator for the full architecture
- Include runtime, memory, tools, gateway, data, network, logging, and observability costs
- Contact sales for custom-trained models and large projects
Pricing checked . Check current pricing at the source ↗
Assessment
Gemini Enterprise Agent Platform strengths and limitations
Where it stands out
- Covers the full agent lifecycle from models and development to runtime, governance, and optimization
- Supports low-code and code-first teams on a common platform
- Strong identity, registry, gateway, evaluation, and audit story for agent fleets
- More than 200 first-party and third-party models reduce single-model lock-in
- Long-running runtime and Memory Bank support stateful, multi-step work
- Deep integration with Google Cloud data, security, infrastructure, and Workspace ecosystem
- Open ADK plus A2A and MCP support provide multiple integration paths
What to consider
- The broad platform and detailed billing model create a steep architecture, security, and FinOps learning curve
- Agent Platform is not the same product as the employee-facing Gemini Enterprise app, and organizations may need both
- Model tokens are only one portion of total cost; runtime, memory, tools, data, gateway, logging, and networking can materially change the bill
- Some models, agent capabilities, regions, or consumption modes may be preview, newly generally available, or subject to changing quotas
- Using open protocols does not eliminate practical dependence on Google Cloud identity, data, runtime, and operational services
- Autonomous multi-step agents still require strong evaluation, approvals, incident response, and human ownership
Compare
Gemini Enterprise Agent Platform alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Agents
Agent Builder
Consider OpenAI Agent Builder when you want a visual multi-agent workflow layer tied to OpenAI's agent tooling.
Explore Agent Builder →Agents
Claude Managed Agents
Consider Claude Managed Agents when Anthropic's agent harness, memory, and orchestration fit the workload and model strategy better.
Explore Claude Managed Agents →Business Operations
Microsoft Copilot
Consider Microsoft's Copilot ecosystem when employee workflows, identity, and enterprise data are primarily centered on Microsoft 365 and Azure.
Explore Microsoft Copilot →Questions
Gemini Enterprise Agent Platform FAQs
What is Gemini Enterprise Agent Platform?
It is Google Cloud's platform for building, deploying, governing, and improving AI agents. It combines models, low-code and code-first tools, managed runtime, memory, security controls, evaluation, and observability.
Did Gemini Enterprise Agent Platform replace Vertex AI?
Google calls it the evolution of Vertex AI and says future Vertex AI services and roadmap developments will be delivered through Agent Platform rather than as a standalone service. Existing ML and generative AI capabilities are part of the broader platform.
Is Agent Platform the same as the Gemini Enterprise app?
No. Agent Platform is the developer and governance foundation. The Gemini Enterprise app is the employee-facing environment for discovering, creating, sharing, running, and monitoring agents.
Which models does it support?
Google says Model Garden offers more than 200 models, including Gemini and Gemma families, Google media models, and supported third-party models such as Anthropic's Claude family.
How much does Gemini Enterprise Agent Platform cost?
There is no single subscription price. Costs depend on model tokens, runtime compute and memory, tools, sessions, stored memories, data services, networking, observability, region, and consumption option. New Google Cloud customers may receive up to $300 in credits.
Does it support MCP?
Yes. Google supports MCP and provides a managed remote MCP server that can let external development tools interact with authorized Agent Platform resources.
Bottom line
Our Gemini Enterprise Agent Platform verdict
Gemini Enterprise Agent Platform is one of the most complete choices for organizations that want agent development and centralized governance on the same cloud foundation. It is strongest for serious Google Cloud estates and regulated multi-team deployments, not teams looking for a simple assistant subscription. Run a narrowly scoped proof of concept and model the entire architecture cost before standardizing.
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