Agent development and deployment
Build and deploy production-ready AI agents and applications using Agent Studio, the Agent Development Kit, and a platform designed to scale with enterprise workloads.
Gemini Enterprise Agent Platform
Freemium
Gemini Enterprise Agent Platform, formerly Vertex AI, is Google Cloud’s platform for developers and technical teams to build, deploy, govern, and optimize AI agents, generative AI applications, and machine learning models.
什么是 Gemini Enterprise Agent Platform？
Gemini Enterprise Agent Platform, formerly Vertex AI, is Google Cloud’s platform for building, deploying, governing, and optimizing enterprise AI agents. It is designed for developers, data scientists, and ML engineers working on agentic systems, generative AI applications, and machine learning workflows.
The platform brings together agent development, access to generative and open models, model customization, evaluation, deployment, and MLOps. Its purpose is to provide a shared environment for moving AI systems from experimentation to production while grounding agents and applications in enterprise data.
Gemini Enterprise Agent Platform 能做什么？
Model Garden and model choice
Discover, test, customize, and deploy Google, third-party, and selected open models through Model Garden, including Gemini, Claude model family, and Gemma models cited on the product page.
Model tuning and evaluation
Customize models with available tuning options and assess generative AI models using Model Evaluation tools intended for objective, data-driven comparison.
Integrated notebooks and data workflows
Use Agent Platform notebooks, including Colab Enterprise or Workbench, with native BigQuery integration to work across data and AI tasks from a shared surface.
MLOps lifecycle management
Manage model projects with tools for training, prediction, pipelines, Model Registry, Feature Store, and monitoring for input skew and model drift.
Agent-powered workflow orchestration
Coordinate multiple agents for workflows such as website code generation, on-brand asset creation, and customer email production through the referenced Agent Platform development tools.
使用场景
“Build enterprise AI agents”
Develop agents grounded in organizational data for applications and workflows that need more than a conversational interface, using Agent Studio or the Agent Development Kit.
“Create generative AI applications”
Use Gemini and other available models to build applications that extract, summarize, or classify information and can be tuned or evaluated before deployment.
“Move models into production”
Train or customize models, evaluate their performance, register them, and deploy them using the platform’s training, prediction, and MLOps capabilities.
“Automate coordinated development work”
Use multiple agents to execute parts of a workflow such as generating website code, producing branded media assets, and drafting customer communications.
“Support data science and ML teams”
Give data scientists and ML engineers a common environment for notebooks, BigQuery-connected data work, model experimentation, pipeline orchestration, and model monitoring.
常见问题
What was Gemini Enterprise Agent Platform previously called?
It was formerly called Vertex AI. The product page describes Gemini Enterprise Agent Platform as the next name for the Vertex AI capabilities now presented within the Gemini Enterprise Agent Platform.
Who is the platform designed for?
It is primarily aimed at developers, data scientists, and ML engineers building AI agents, generative AI applications, and machine learning systems.
Can teams use models other than Google’s Gemini models?
Yes. The product page describes Model Garden as offering Google models, third-party models such as Anthropic’s Claude model family, and selected open models such as Gemma.
Does the platform support both custom training and managed model workflows?
Yes. Custom training supports preferred open-source frameworks, custom training code, and hyperparameter tuning options. The platform also provides managed capabilities for training, prediction, evaluation, pipelines, model registration, feature management, and monitoring.
How is Agent Platform priced?
Google Cloud uses pay-as-you-go pricing, so costs depend on the services and usage involved. New customers can receive up to $300 in Google Cloud credits to try Agent Platform and other Google Cloud products. Google provides a pricing calculator and sales-based quotes for more detailed estimates.
快速信息
- Product type
- Enterprise AI agent, generative AI, and machine learning platform
- Former name
- Vertex AI
- Primary users
- Developers, data scientists, and ML engineers
- Core workflows
- Build agents, train and tune models, evaluate models, and deploy to production
- Model access
- Google, third-party, and selected open models through Model Garden
- Pricing model
- Google Cloud pay-as-you-go pricing; costs vary by product and usage
Gemini Enterprise Agent Platform 替代品
Kopai
usekopai.com
Kopai is a hosted platform for building, running, publishing, and monetizing domain-specific AI agents. It supports internal team agents, marketplace listings, and deployment to a creator’s own site through live APIs.
Gemini Enterprise Agent Platform
cloud.google.com
Gemini Enterprise Agent Platform is Google Cloud’s platform for developers and technical teams to build, deploy, scale, govern, and optimize enterprise AI agents and generative AI applications using enterprise data.
Context
context.ai
Context 是企业级 AI 智能体平台，可在客户基础设施上构建、部署和改进智能体，并提供工作区、运行时、上下文、评估工具、连接器及基于 IdP 的访问控制。
OneReach.ai
onereach.ai
OneReach.ai GSX 是面向企业的智能体编排平台，可大规模构建、运行和治理 AI 智能体。
Octomind Cloud
octomind.run
Octomind Cloud runs AI agents on persistent cloud machines for research, writing, web work, software development, and scheduled routines. Users give instructions in plain language and can receive results through the web panel, Telegram, WhatsApp, or Slack.
Stagehand
www.stagehand.dev
Stagehand is an SDK for building browser agents with Playwright-style APIs, natural-language actions, structured extraction, and self-healing behavior. It supports TypeScript, Python, and Go for agents that need to operate web pages with browser-level control.