Vertex AI Agent Builder

Vertex AI Agent Builder is Google’s suite of tools for building, deploying, scaling, and governing production AI agents. It provides developers with tools for creating enterprise-ready agents using Google’s AI models, open-source frameworks, enterprise data, retrieval systems, and agent runtime infrastructure.

Google announced Vertex AI Agent Builder in April 2024, bringing together Vertex AI Search and Conversation capabilities with additional tools for building generative-AI applications and agents.

The platform supports different development approaches, ranging from natural-language and low-code experiences to developer frameworks such as Google’s Agent Development Kit (ADK) and open-source frameworks such as LangChain. This allows teams to build agents according to their technical requirements rather than relying on one development method.

A major part of Agent Builder is its ability to connect AI agents to enterprise information. Developers can use Vertex AI Search, retrieval-augmented generation (RAG), document processing, ranking, retrieval, and grounding capabilities to provide agents with relevant business information. Agents can also use Google Search for grounding where supported.

The platform includes Agent Engine, a managed runtime designed for deploying and operating agents in production. It provides infrastructure for running agents while supporting enterprise requirements around scaling, monitoring, sessions, memory, and governance.

Agent Builder also supports agent evaluation and observability, helping developers assess agent behavior and monitor production systems. Google’s broader platform is designed to support the lifecycle from development and experimentation through deployment, scaling, and governance.

The platform supports grounding and RAG to improve the reliability of generated responses. Developers can use retrieval APIs for document layout processing, ranking, retrieval, and checking grounding outputs. Vector search can also be used for embedding-based applications and agents.

Google has also expanded its support for multilingual grounding. The grounding API supports more than 35 languages for applicable functionality, although exact language availability depends on the particular feature and model.

Current Product Naming

There has been a naming change that is important for a directory listing. Google originally used Vertex AI Agent Builder as the name for the product announced in 2024. In 2025, Google renamed the original Agent Builder product to AI Applications, while the broader agent-building capabilities continue to be developed within Google’s current agent platform.

Google’s current documentation now describes Vertex AI Agent Builder as a suite of products that helps developers build, scale, and govern AI agents in production, with documentation covering Agent Builder, the Agent Development Kit, and Agent Engine.

Pricing

Vertex AI Agent Builder follows Google Cloud’s usage-based pricing structure rather than a simple fixed monthly subscription. Costs depend on the individual services and resources used to build and operate agents.

Agent Engine, for example, has separate charges for runtime resources, memory, code execution, stored session events, and memory-related services. Google reduced the Agent Engine runtime price to $0.0864 per vCPU/hour and $0.0090 per GB-hour of memory in December 2025. Additional Agent Engine services began incurring charges in January 2026.

Other costs can come from the underlying Gemini models, Vertex AI Search, grounding, storage, vector search, and other Google Cloud services used by an agent.

New Google Cloud customers can start a proof of concept with $300 in free credits, with no automatic charges or commitment.

Pricing Model

Paid

Pricing Note

Vertex AI Agent Builder uses Google Cloud’s usage-based pricing. The final cost depends on the agent components and Google Cloud services used, including model inference and Agent Engine resources. New customers can use $300 in Google Cloud credits for a proof of concept.

Review

Vertex AI Agent Builder is a strong choice for developers and organizations that want to build production-grade AI agents within Google Cloud. Its biggest advantage is that it combines agent development frameworks, enterprise search, RAG, grounding, deployment, scaling, evaluation, and governance within one ecosystem.

The platform is particularly useful for teams that need agents to work with enterprise data. Vertex AI Search and RAG capabilities provide mechanisms for grounding agent responses in organizational information instead of relying solely on a model’s training data.

Its support for multiple development frameworks is another advantage. Developers can use Google’s Agent Development Kit or other supported frameworks, while less technical users can use more accessible agent-building experiences.

Agent Engine also makes the platform more suitable for production deployments because Google provides managed infrastructure for running agents at scale. The platform has continued expanding its capabilities around runtime management, sessions, memory, code execution, and governance.

The main drawback is complexity. Vertex AI Agent Builder is primarily an enterprise developer platform rather than a simple consumer chatbot builder. Understanding Google Cloud services, authentication, data sources, model pricing, deployment, and governance may require technical expertise.

Pricing can also become difficult to forecast because multiple Google Cloud services may contribute to the total cost of an agent.

For organizations already using Google Cloud, Vertex AI Agent Builder provides a comprehensive environment for moving AI agents from prototypes into production.