Vertex AI

Google Cloud

Google Cloud's model and ML platform: Gemini plus open models, tuning, RAG and agents under GCP IAM — Bedrock's twin when the data already lives in BigQuery.

Product preview

Overview

Vertex is Google's answer to “the model should sit next to the warehouse”: Gemini for the new work, open models for the rest, tuning jobs, Search for RAG, Agent Builder for the click-ops crowd, all billed in a GCP project. Bedrock is the AWS rhyme; Azure AI Studio is the Microsoft one.

The tax is GCP fluency and a console that still feels like several products taped together. Gemini via Vertex is not always the same Gemini you get at aistudio.google.com. If BigQuery is already the source of truth, calling OpenAI from a laptop is the harder architecture.

Pros / Cons

Pros

Gemini next to BigQuery under one IAM
Tuning and RAG without a second vendor
Residency and VPC-SC for regulated data
Default when the warehouse is already GCP

Cons

Console still feels like several products
Gemini-on-Vertex can lag AI Studio
GCP fluency is not optional

Who it's for

Gemini inference inside a GCP project

RAG over BigQuery and documents

Tuning an open model on Vertex jobs

Agent Builder for click-ops teams on GCP

Bottom line

Enterprise Gemini next to BigQuery — pick it when the warehouse is already Google Cloud.

Key Features

Gemini and third-party models on one platform

Tuning and distillation jobs

Vertex Search / RAG tooling

Agent Builder

GCP IAM, VPC-SC and data residency

Compare Vertex AI with alternatives

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Frequently asked questions

What is Vertex AI?

Vertex AI is a AI Platforms tool developed by Google Cloud. The company was founded in 2021 and is headquartered in Mountain View, USA. Google Cloud's model and ML platform: Gemini plus open models, tuning, RAG and agents under GCP IAM — Bedrock's twin when the data already lives in BigQuery.