Google Vertex AI Tutorial: How To Build AI Agents [2026]

Unlike chatbots, generative AI agents—also known as agentic AI—are set to revolutionize AI architecture by autonomously handling complex tasks that typically require human intervention.

In April 2024, Google Cloud introduced Vertex AI Agent Builder, a tool that lets you create AI-powered conversational agents without writing any code.

But Vertex AI offers much more than just an AI agent builder. This article will walk you through all you need to know about Google Vertex AI—its features, pricing, how to use the platform, and best alternatives like Voiceflow.

What’s Vertex AI?

Vertex AI is Google Cloud’s fully managed platform designed for building, deploying, and managing machine learning and generative AI models.

First launched in May 2021, Vertex AI simplifies the entire machine learning workflow for businesses and developers by integrating a wide range of tools and services into a single, cohesive platform.

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Here’s an in-depth look at its capabilities:

• End-to-End ML Model Management: Train, test, tune, and deploy machine learning models on a single platform. Vertex AI supports 150+ foundation models including Gemini 1.5 Pro.
• MLOps Integration: Automate, standardize, and manage machine learning projects with MLOps tools. This ensures continuous integration and deployment (CI/CD) of models.
• Generative AI with Gemini: Quickly build and deploy generative AI applications using Gemini, which enhances performance with long context understanding and multimodal capabilities, enabling the integration of audio, video, text, and code inputs.
• Enterprise-Ready AI Agents: Vertex AI’s no code conversational AI builder supports the creation of sophisticated AI agents that can handle complex tasks.
• Specialized AI Solutions: Deploy Google Cloud’s AI solutions, such as Anti Money Laundering AI, easily. These pre-built solutions help businesses address specific challenges with minimal setup.

Vertex AI Model Garden

Vertex AI’s Model Garden is where you can easily access 150+ foundation models, fine-tunable models, and pre-built models for task-specific solutions, including:

• Gemini 1.5 Pro
• Gemini 1.5 Flash
• Stable Diffusion v1-5
• PaLM 2 Chat Bison
• BiomedCLIP

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Vertex Generative AI Studio

The Vertex Generative AI Studio allows you to create, fine-tune, and deploy generative AI models.

Once you select a model in the Vertex Model Garden, click on “Open Prompt Design” and it’ll bring you to the Generative AI Studio. You can interact with the model via a simple UI, or tune the model with your own data.

The Generative AI Studio allows you to focus on fine-tuning and customization rather than building models from scratch.

Vertex AI Agent Builder

Vertex AI is a platform for building, deploying, and managing intelligence search and conversation applications.

Here are the key features of Vertex AI’s Agent Builder:

• Advanced Integrations: Supports integrations with frameworks like LlamaIndex and LangChain for enhanced AI capabilities.
• RAG: Uses Retrieval Augmented Generation to combine LLM-generated responses with real-time data retrieval and enterprise data for more accurate and context-aware interactions.
• NLU: Advanced natural language understanding for accurate query responses, supporting multiple languages.
• No-code Development: Use the visual drag-and-drop interface to create AI agents without a single line of code.

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Vertex AI Agent Use Cases

There are four types of agents that you can build using Google’s Vertex AI:

1. Customer agents: travel booking, manage orders, FAQ bots
2. Employee agents: employee onboarding, invoice payments, inventory management
3. Knowledge agents: legal, sales, customer support
4. Voice agents: contact center, food ordering, automobiles

What Are the Disadvantages of the Vertex AI Agent Builder

Vertex AI Agent Builder, while powerful, has some limitations. It offers less customization than building agents from scratch, may struggle with scalability for highly complex applications, and is heavily dependent on Google Cloud services. There can be an initial learning curve despite its no-code interface, and extensive use of advanced features may lead to higher costs.

Vertix AI Pricing

Vertex AI offers a free tier with limited usage, allowing you to try out the platform at no cost. This free tier includes a specific amount of usage for services like training and predictions. Beyond the free tier, pricing is based on your usage of various services, such as training hours, prediction hours, and data storage. For example, model training starts at $0.10 per training hour for standard models. For additional data, such as video, text, image processing, rates range from $0.0001 to $0.008 per unit.

Vertex AI Competitors and Alternatives

There are several free and paid alternatives to the Google Vertex AI Agent Builder, including Voiceflow, Dialogflow, Rasa, Amazon Lex, and IBM Watson Assistant.

If you’re looking for the best free alternative to Vertex AI Agent Builder, choose Voiceflow—the number one AI agent builder trusted by 250,000+ teams, from Home Depot to LVMH. Here’s why:

• No-Code Development: Easily create conversational agents with a visual interface.
• Cross-Platform Compatibility: Build once and deploy across multiple platforms like Alexa, Google Assistant, and web.
• Collaboration Tools: Enhanced team collaboration features for shared project development.
• Extensive Integrations: Seamlessly integrates with various APIs and backend systems.
• User-Friendly Interface: Intuitive design making it accessible to non-developers.
• Community and Support: Strong user community and robust support resources.

With Voiceflow, you can build and launch a custom AI agent in 10 minutes without writing a line of code. Get started today—it’s free!

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Frequently Asked Questions

Vertex AI API

The Vertex AI API allows developers to integrate machine learning models into their applications easily. You can use it to train, deploy, and manage ML models at scale. Learn more here.

What is GCP?

GCP, or Google Cloud Platform, is a suite of cloud computing services offered by Google. It provides infrastructure, platform, and software services to help businesses scale and innovate.

What’s the Vertex AI Feature Store?

The Vertex AI Feature Store is a managed repository for storing, sharing, and managing machine learning features. It helps streamline the development and deployment of ML models by providing a consistent set of features.

Vertex AI vs. AWS Sagemaker

Vertex AI and AWS Sagemaker both offer comprehensive tools for building, training, and deploying ML models. However, Vertex AI is deeply integrated with Google Cloud services, while Sagemaker is tailored for AWS environments.

Vertex AI vs. Bard

Vertex AI is a platform for developing and deploying machine learning models. Bard is a large language model developed by Google AI for natural language understanding and generation tasks.

Vertex AI vs. Kubeflow

Vertex AI is a managed service offering end-to-end machine learning capabilities, while Kubeflow is an open-source platform designed to simplify deploying machine learning workflows on Kubernetes.

Vertex AI vs. Bedrock

Vertex AI is Google Cloud’s fully managed ML platform, while Bedrock is Amazon’s offering for foundational AI models, focusing on customizable and scalable AI solutions within AWS.

Vertex AI vs. ChatGPT

Vertex AI is a platform for developing, deploying, and managing various ML models, including generative AI, while ChatGPT, developed by OpenAI, is a specific large language model optimized for conversational tasks.

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