Google Cloud's managed platform for building and deploying AI agents with grounding in enterprise data, Google Search, and custom knowledge bases.
Google Cloud's platform for building AI agents and search apps using your own data — enterprise-grade with Google's AI behind it.
Google Vertex AI Agent Builder is a managed platform within Google Cloud for building, deploying, and scaling AI agents grounded in enterprise data. It provides a comprehensive set of tools for creating agents that can search enterprise knowledge bases, answer questions from company documents, and complete tasks using Google's foundation models.
The platform offers multiple agent types: conversational agents for customer and employee interactions, search agents for enterprise knowledge retrieval, and generative agents that can create content and complete complex tasks. Agents are powered by Gemini models with built-in grounding capabilities that reduce hallucination by connecting responses to verified data sources.
Vertex AI Agent Builder's data connectors ingest content from websites, Cloud Storage, BigQuery, third-party platforms, and custom APIs to build searchable knowledge bases. The platform handles chunking, embedding, indexing, and retrieval automatically, providing enterprise-grade RAG (Retrieval Augmented Generation) without custom infrastructure.
For developers, the platform integrates with Google ADK (Agent Development Kit) for code-first agent development, while also providing a no-code console for building simpler agents. Deployment options include web widgets, API endpoints, Dialogflow CX integration, and Google Chat. The platform includes built-in analytics showing query patterns, answer quality, and user satisfaction.
Enterprise features include VPC Service Controls, Customer-Managed Encryption Keys (CMEK), IAM integration, and compliance with Google Cloud's security certifications. Vertex AI Agent Builder represents Google's enterprise-ready agent platform, competing directly with AWS Bedrock Agents and Azure AI Agent Service.
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Ground agents in company documents, websites, BigQuery datasets, and custom data sources to ensure responses are based on verified organizational knowledge.
Use Case:
Automatic document chunking, embedding, indexing, and retrieval — enterprise-grade RAG without building custom vector search infrastructure.
Use Case:
Build conversational agents, search agents, and generative agents with different capabilities optimized for specific use cases.
Use Case:
Agents powered by Google's latest Gemini models with built-in grounding and hallucination reduction capabilities.
Use Case:
Console-based builder for simple agents plus ADK integration for complex code-first development — supporting both business users and developers.
Use Case:
VPC Service Controls, CMEK, IAM integration, and Google Cloud compliance certifications for regulated industry deployments.
Use Case:
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View Pricing Options →Enterprise knowledge base search and Q&A agents
Customer support agents grounded in product documentation
Internal employee assistants connected to company data
Google Cloud-native agent deployments
We believe in transparent reviews. Here's what Google Vertex AI Agent Builder doesn't handle well:
ADK is an open-source framework for building agents in code. Vertex AI Agent Builder is a managed cloud platform that can use ADK-built agents or provide no-code agent creation with managed hosting.
Vertex AI Agent Builder primarily uses Gemini models. For other models, you'd use Vertex AI's Model Garden or bring custom models, but the agent builder is optimized for Gemini.
You connect data sources (documents, websites, databases) and the platform automatically chunks, embeds, and indexes content. Agents retrieve relevant context before generating responses.
Dialogflow CX is for structured conversational flows. Agent Builder adds generative AI capabilities, enterprise search, and flexible agent types beyond traditional chatbots.
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