Google Vertex AI Agent Builder: An Overview
An overview of Google Vertex AI Agent Builder: a Google Cloud platform for building, deploying, and governing production AI agents at scale.
Google Vertex AI Agent Builder is Google Cloud's platform for building, deploying, and governing production AI agents. It brings together a code-first development kit, a managed runtime, model access, persistent memory, and enterprise governance into a single offering. This overview explains what the platform includes and how its pieces fit together.
What Vertex AI Agent Builder Is
Vertex AI Agent Builder is the enterprise agent layer within Google Cloud's broader Vertex AI platform. Rather than a single tool, it bundles several components: a development framework for writing agents in code, a low-code visual builder for assembling them more quickly, access to a wide range of foundation models including Gemini and selected third-party models, and a managed runtime for hosting agents in production.
The platform has evolved alongside Google's broader agent strategy and has been folded into Google's enterprise agent offerings announced at its cloud events. The goal is to give organizations one place to move from prototype to governed, production-grade agents without stitching together many separate services.
The Agent Development Kit
A central component is the Agent Development Kit, or ADK, an open-source framework for building, debugging, and deploying agents. ADK is code-first and available in multiple languages, giving developers precise control over agent behavior, tool use, and multi-agent orchestration. It is model-agnostic, so it can be used with Gemini, third-party models, or open models, and it can be deployed to containers or Kubernetes environments rather than being locked to a single runtime.
ADK is designed with multi-agent systems in mind. Developers can compose specialized agents into hierarchies, define supervisor agents that route tasks to sub-agents, and build predictable pipelines or more dynamic, agent-coordinated routing. It also includes a rich tool ecosystem for integrating third-party services and custom code, plus tooling for evaluating and scaling agents.
Runtime, Memory, and Governance
Beyond building agents, Vertex AI Agent Builder provides Agent Engine, a managed runtime that handles deployment and scaling so teams do not have to operate the infrastructure themselves. The platform supports persistent memory, allowing agents to retain context across sessions, and it has added features such as restoring state after errors and pausing for human input inside complex workflows.
Governance is a major emphasis for enterprise customers. The platform includes controls over which tools agents can use and how they operate, giving security and platform teams the oversight they need to deploy agents responsibly. This combination of building, running, and governing in one place is what distinguishes a full platform from a standalone framework.
Who It Is For
Vertex AI Agent Builder suits organizations on Google Cloud that want an integrated path from agent development to governed production deployment. The open-source ADK can be used independently, which gives teams flexibility, while the managed runtime and governance features are tied to Google Cloud. Pricing follows Google Cloud's consumption-based model tied to compute and model usage.
Frequently Asked Questions
Is the Agent Development Kit open source?
Yes. ADK is an open-source, code-first framework available in several languages, and it can be used independently of the rest of Vertex AI Agent Builder.
Can Vertex AI Agent Builder use models other than Gemini?
Yes. The platform provides access to a wide range of models, and ADK is model-agnostic, so it can work with Gemini, open models, and selected third-party models.
What is Agent Engine?
Agent Engine is the managed runtime that handles deploying and scaling agents in production, so teams do not have to operate the underlying infrastructure themselves.