Vertex AI

in English: Google Vertex AI

advancedwidespread

Vertex AI is Google's cloud service where companies can rent artificial intelligence models, adapt them to their own data, and build applications and agents on top of them.

In plain terms

Imagine it as a fully equipped industrial kitchen you can rent. You don't need to buy your own oven, cold room and cook: you walk in, use the professional equipment, and pay only for what you actually use. Vertex AI offers the same for artificial intelligence: the expensive computers and ready-made models sit in Google's data centers, and the company reaches them over the internet.

It is used by companies to build their own AI solutions: a customer service chatbot, a document processor, an internal search tool, or an agent that independently completes multi-step tasks. On the platform, models from other providers and open-source communities are available alongside Google's own models (such as Gemini).

It differs from a chat application in that it is not built for the end user. You rarely see it directly because it works in the background: it is the workshop and machine room for those developing and operating AI-based services.

How it works

The company opens an account on Google Cloud, selects a model from the platform's catalog (Model Garden), or uploads its own.
Developers test the model: they write instructions for it, test its answers, and if necessary fine-tune it with the company's own data or connect it to the internal document repository.
The ready-made solution is integrated into the company's website, application, or internal system via a programming interface (API).
When an agent is built, it is specified which tools it can use (for example search, a database, a calendar), and the platform runs and supervises it.
Google provides computing capacity, scalable expansion based on load, logging, and access management; the company typically pays after actual usage, but large users can also purchase pre-booked capacity.

An everyday example

You ask a web store chat window where your package is, and within seconds you get a precise, natural-sounding answer. It may be that a model running on Vertex AI read your order data and formulated the answer in the background, but you only see the store.

Who is affected

developerFor them, this is their daily work tool: here they select a model, test it, and integrate it into the application. → Code

entrepreneur, executiveThey decide which cloud provider the company's AI solutions are built on, which involves costs, data handling, and long-term dependency.

employeeSuch a platform often sits behind a company's internal assistant or document search, so you work with it indirectly. → Work & HR

everyoneAs a customer, you use many services whose AI functions run on such cloud platforms, and your data may also end up there.

A common misconception

MythVertex AI itself is an artificial intelligence, something like Gemini or ChatGPT.

In realityVertex AI is not a model but a platform: it is the environment where models (including Gemini) are accessed, customized, and operated. Gemini is the engine; Vertex AI is the workshop and garage around it.

Limits and risks

The cost grows with usage and is hard to estimate: the bill for a successful, heavily used application can quickly spike.
Anyone building everything on this is tied to Google, and switching to another provider later involves much work and money.
The platform does not make models more reliable: AI running here can still err or hallucinate; verifying the output remains the company's responsibility.
A European company must pay particular attention to which region stores and processes its data: the GDPR attaches strict conditions to the transfer of personal data outside the EU, and certain sectoral regulations explicitly require local storage.

Similar, but not the same

Gemini – Gemini is Google's model family and chat application, while Vertex AI is the enterprise platform through which Gemini and others can be accessed.
Google AI Studio – AI Studio is a fast, simple experimentation interface for individual developers, while Vertex AI is the version for enterprise operations with security and oversight tools.
Amazon Bedrock – A similar service, but on Amazon's cloud and with a partially different model offering; the two are competitors.

Related concepts

Broader

cloud service, AI-platform, AI infrastructure, machine learning platform

Narrower

Model Garden, Vertex AI Agent Builder, fine-tuning, model deployment

On the edge

Amazon Bedrock, Microsoft Foundry (formerly Azure AI Foundry), Gemini, API, MLOps

A brief history

Google introduced Vertex AI in May 2021 at the Google I/O developer conference to consolidate its previously scattered machine learning cloud tools. With the rise of generative AI, large language models and agent building became the focus from 2023. In spring 2026, Google presented an upgraded version of the platform under the name Gemini Enterprise Agent Platform.

Where things stand

At the end of 2026, it is one of the three leading enterprise AI cloud platforms, alongside similar services from Amazon and Microsoft. The emphasis has shifted from access to models to building and running agents. In 2026, Google continued Vertex AI under the name Gemini Enterprise Agent Platform, but the Vertex AI name is still widely used in everyday speech and in many descriptions, so you may encounter it under both names.

Status: 2026 November

In the news

Appears in 1 Agent Age stories; the curve shows weekly occurrence in the news magazine.

Vertex launches Vertex Sōl, an AI-powered tax and compliance platformOct 26, 2026 · Money

Also known as

Vertex AI · Google Vertex AI · Google Cloud Vertex AI · Vertex · Vertex AI platform · Vertex AI Studio · Vertex AI Agent Builder · Gemini Enterprise Agent Platform · Google's AI cloud platform

Sources

This entry was machine-edited and has undergone machine expert review; the “In the news” section updates automatically from Agent Age stories.