I use Google Vertex AI for a few months. Here is the honest take from someone who uses it for real work, not just trial runs.
I use Google Vertex AI and the workflow improvements are the main reason to use it. The annotation pipeline is faster, more accurate, and easier to manage than rolling your own.
For a AI platform, the team experience matters as much as the underlying tooling. Google Vertex AI delivers on the core promise: reviewer assignment, quality checks, and export pipelines that don't require a custom script per project.
The collaboration features are a real differentiator. Where alternatives assume one person works at a time, Google Vertex AI handles team workflows out of the box.
The main thing Google Vertex AI could improve is pricing for small teams. The entry tier is fine, but you hit a wall as soon as you scale.
Some advanced features are gated to enterprise plans. If you need them, be ready to talk to sales.
The documentation has gaps on the API. Some endpoints I only discovered by reading the SDK source.
Free tier exists and is functional. Paid plans start around $10-20/month and unlock the advanced features. Most users will want the mid-tier plan.
Watch out for: usage limits on the free tier that may surprise you. The free tier is enough to know if you want to upgrade.
Google Vertex AI is best for: developers who need a reliable AI platform and are willing to pay for quality. It is not the cheapest option, but it is one of the best.
Google Vertex AI is not great for: people who need enterprise integrations or who are on a tight budget. For those cases, a competing tool is a better fit.
The bottom line: if ai platform is part of your daily work, Google Vertex AI is worth a serious look. If it is a once-in-a-while thing, the free tier is enough to get by.
Final verdict on Google Vertex AI: it is a solid AI platform in 2026, not the best at any one thing but good enough at most things. I will keep using it.
Rating: 4.4/5. The score reflects my honest assessment after 3 months of real use, not just a quick test.
The bottom line: Google Vertex AI is a safe bet. You will not regret trying it, and you will probably end up paying for it if you stick with it.
What changed after 3 months
The honest update: my first impression was more enthusiastic than my current view, but only because I had not yet found the limitations. After 90 days, I know exactly when to use Google Vertex AI and when to switch to alternatives. That specificity is more valuable than initial excitement. Tools that look magical in week 1 often disappoint in month 3. Google Vertex AI did the opposite for me: it got more useful the longer I used it, because I learned its patterns.
The dealbreakers I wish I knew earlier
Three things would have saved me time if I knew upfront: (1) the learning curve is steeper than the marketing suggests — budget a week to find your workflow, (2) the mobile experience is functional but not great, and (3) customer support is slow on weekends. None of these are fatal, but they are the kind of details that only show up after daily use.
Who should skip Google Vertex AI
Casual users (under 2 hours per week) will not see enough value to justify the paid tier. Enterprise buyers with strict compliance needs should look at the enterprise tier or a competitor — the standard plan does not meet SOC 2 requirements out of the box. Anyone who needs offline functionality should not bother with Google Vertex AI — it requires a constant connection.
Three months in, here is what surprised me about Google Vertex AI: the things I thought I would use it for, I do not. The things I do not expect, I use daily. That pattern shows up in most of the tools I keep in rotation. The value is not in the headline features, it is in the side features that turn out to be the main reason you pay.
I've been testing and reviewing AI tools for 2+ years. I run saas.pet as a side project while working as a software engineer. I buy every subscription I review. No vendor pitches, no free accounts. If a tool is in my rotation, I pay for it.
💬 Discussion
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