Avis sur Vertex AI 2026 : Avantages, Inconvénients, Fonctionnalités et Tarification

Managing AI projects across multiple tools and cloud services can quickly become complex, especially as models scale and teams grow. Vertex AI is a machine learning software platform on Google Cloud that brings data preparation, training, deployment, and monitoring into one managed environment. It supports both predictive and generative AI workloads, helping teams reduce workflow fragmentation and operate at scale.

In this review, you’ll get an overview of Vertex AI’s features, use cases, pros and cons, and pricing to decide if it fits your needs.

Vertex AI Evaluation Summary

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Vertex AI Overview

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Our Review Methodology

How We Test & Score Tools

We’ve spent years building, refining, and improving our software testing and scoring system. The rubric is designed to capture the nuances of software selection and what makes a tool effective, focusing on critical aspects of the decision-making process.

Below, you can see exactly how our testing and scoring works across seven criteria. It allows us to provide an unbiased evaluation of the software based on core functionality, standout features, ease of use, onboarding, customer support, integrations, customer reviews, and value for money.

Core Functionality (25% of final scoring)

The starting point of our evaluation is always the core functionality of the tool. Does it have the basic features and functions that a user would expect to see? Are any of those core features locked to higher-tiered pricing plans? At its core, we expect a tool to stand up against the baseline capabilities of its competitors.

Standout Features (25% of final scoring)

Next, we evaluate uncommon standout features that go above and beyond the core functionality typically found in tools of its kind. A high score reflects specialized or unique features that make the product faster, more efficient, or offer additional value to the user.

We also evaluate how easy it is to integrate with other tools typically found in the tech stack to expand the functionality and utility of the software. Tools offering plentiful native integrations, 3rd party connections, and API access to build custom integrations score best.

Ease of Use (10% of final scoring)

We consider how quick and easy it is to execute the tasks defined in the core functionality using the tool. High scoring software is well designed, intuitive to use, offers mobile apps, provides templates, and makes relatively complex tasks seem simple.

Onboarding (10% of final scoring)

We know how important rapid team adoption is for a new platform, so we evaluate how easy it is to learn and use a tool with minimal training. We evaluate how quickly a team member can get set up and start using the tool with no experience. High scoring solutions indicate little or no support is required.

Customer Support (10% of final scoring)

We review how quick and easy it is to get unstuck and find help by phone, live chat, or knowledge base. Tools and companies that provide real-time support score best, while chatbots score worst.

Customer Reviews (10% of final scoring)

Beyond our own testing and evaluation, we consider the net promoter score from current and past customers. We review their likelihood, given the option, to choose the tool again for the core functionality. A high scoring software reflects a high net promoter score from current or past customers.

Value for Money (10% of final scoring)

Lastly, in consideration of all the other criteria, we review the average price of entry level plans against the core features and consider the value of the other evaluation criteria. Software that delivers more, for less, will score higher.