Vertex AI

Vertex AI is Google Cloud’s unified platform for building, deploying, and scaling machine learning and generative AI. It brings together access to foundation models like Gemini, a Model Garden of pre-built models, AutoML for custom training, and full MLOps tooling — plus vector search and agent-building capabilities for modern AI apps. For enterprises and developers who want to build and run AI on Google Cloud, from custom ML to generative AI and agents, Vertex AI is a comprehensive backbone.

What is Vertex AI?

Vertex AI is Google Cloud’s unified platform for building, deploying, and scaling machine learning and generative AI applications, serving as an end-to-end MLOps solution (and increasingly positioned around building AI agents). Its features include generative-AI integration with built-in access to Gemini and other foundation models; Model Garden, a curated collection of pre-built models with fine-tuning; AutoML for automated custom model training; Vertex Workbench (managed Jupyter notebooks); push-button model deployment and serving with automatic scaling; MLOps pipelines for orchestration and monitoring; Vector Search for similarity search and retrieval-augmented generation (RAG); prompt-engineering tools; and enterprise safety and governance controls. It serves enterprise organizations, data scientists and ML engineers, developers integrating generative AI, and teams needing MLOps governance. Vertex AI uses Google Cloud usage-based pricing with a free tier or credits to start.

What it does well

• Foundation models: built-in Gemini and Model Garden.
• Full lifecycle: AutoML, deployment, and MLOps pipelines.
• AI-app ready: vector search for RAG and agent tools.
• Enterprise-grade: governance, safety, and scaling.

Who it is for

Vertex AI fits enterprises, data scientists, ML engineers, and developers — especially those on Google Cloud — who need to build, deploy, and scale custom ML models and generative-AI applications, from training and MLOps to RAG and agents, with enterprise governance. Its breadth suits organizations building serious AI. Small teams with light needs, or those not on Google Cloud, may find it heavier than necessary, and it requires cloud and ML expertise, but for enterprise ML and generative AI on Google Cloud, Vertex AI is a powerful, comprehensive choice with a free tier to start.

Things to keep in mind

• It is an enterprise cloud platform with a learning curve.
• Usage-based pricing means costs scale with compute and services.
• Full value comes for teams building on Google Cloud.

Our verdict

Vertex AI is a comprehensive, enterprise-grade platform for machine learning and generative AI on Google Cloud, and its scope is its strength: built-in access to Gemini and a Model Garden, AutoML for custom training, full MLOps pipelines, model deployment with autoscaling, and vector search plus agent tools for modern AI apps — all with enterprise governance. For organizations building serious AI on Google Cloud, that end-to-end coverage is compelling. It has a learning curve and usage-based costs, but for enterprise ML and generative AI on Google Cloud, Vertex AI is an excellent choice.

Frequently asked questions

What is Vertex AI?

Vertex AI is Google Cloud’s unified platform for building, deploying, and scaling machine learning and generative AI, with access to Gemini, Model Garden, AutoML, and MLOps tooling.

What generative AI does Vertex AI offer?

It offers built-in access to Gemini and other foundation models, a Model Garden with fine-tuning, vector search for RAG, prompt tools, and agent-building capabilities.

Is Vertex AI free?

Vertex AI uses Google Cloud usage-based pricing across its services, with a free tier or credits to get started.

Who is Vertex AI for?

It is for enterprises, data scientists, ML engineers, and developers building and scaling custom ML and generative AI on Google Cloud with enterprise governance.