"Build, train, and deploy ML and generative AI models—no expertise required"
Typical plan: $250 / month

Build, train, and deploy ML and generative AI models—no expertise required
Based on user reviews
Rating Distribution
Anonymous
3 months ago
Been working with Vertex AI for about 3 months on demand forecasting. The BigQuery integration is genuinely smooth and cuts data prep time significantly. Main frustration? Documentation feels scattered across different Google Cloud pages, made custom training setup more painful than it should've been. AutoML features work well for straightforward tasks though.
Marcus Chen
3 months ago
Been experimenting with Vertex AI for about three months now, mostly on demand forecasting models. The unified workflow is genuinely impressive - everything from data prep through deployment happens in one place, which beats jumping between tools. BigQuery integration is seamless. The learning curve gets steep once you move beyond AutoML though. Advanced custom training configurations left me hunting through fragmented docs. Pricing scales fairly, though frequent retraining can add up. For straightforward projects, it's excellent. Complex setups? Expect some friction.
Join 10,000+ users who trust our reviews
Sign up to see all reviews and get insights from real users
Already have an account? Log in
Building and training ML models with Vertex AI
Dr. William Bobos
Dr. William Bobos has reviewed Google Cloud AutoML for Data Analytics, rating it 4.0/5 based on 2 user reviews. This tool is particularly well-suited for AI tools use cases, making it a strong choice for business executives in this field.
Pricing: $0 – $5,700 / month(Updated January 2026)
Free tier with $300 credits for 90 days. AutoML training from $0.20-$7.89/node hour (varies by machine type), prediction from $0.02-$0.50 per 1,000 requests. Estimated monthly costs range from $0 (free tier) to $5,700+ depending on usage. Enterprise plans available via contact.
Usage Model: Pay-as-You-Go — ensuring you only pay for what you actually use.
Google Cloud AutoML's free tier enables business executives to experience data analytics capabilities at no cost. The free plan provides essential functionality that's ideal for learning and initial testing. Paid plans expand capabilities significantly, offering advanced features, higher capacity, and dedicated support for business executives with professional data analytics requirements.
Google Cloud AutoML is now integrated into Google Cloud Vertex AI, a unified machine learning platform that enables users of all skill levels to build, train, evaluate, and deploy high-quality custom models for vision, language, structured data, and generative AI with minimal coding. Vertex AI combines AutoML, custom training, MLOps capabilities, and access to Google's Gemini and over 200 foundation models from Model Garden in a scalable, cloud-native environment with end-to-end tools for data preparation, model evaluation, and serving. Legacy standalone AutoML products are deprecated; all new AutoML functionalities and pre-trained models are accessed through Vertex AI.[1][4][6]
Understanding the core functionality and approach of Google Cloud AutoML.
Pay-as-you-go pricing means Google Cloud AutoML costs scale with your actual usage. No wasted spend on unused seats or features you don't need yet. Integrations with Plugin/Integration keep work connected.
Explore the powerful features that make Google Cloud AutoML stand out.
Rate limits and authentication are clearly documented for smooth implementation.
SDKs for Python and JavaScript/TypeScript remove boilerplate and shorten the path to production.
Discover how different audiences leverage Google Cloud AutoML for their specific needs.
Product teams lean on Google Cloud AutoML to test features, gather feedback, and prioritize roadmaps using real data.
Discover more AI tools in related categories, platforms, and use cases.
Deepen your understanding of the concepts behind tools like Google Cloud AutoML with our expert guides.
Understand core concepts like LLMs and Machine Learning.
Master search, filtering, and comparison to find the perfect tool.
Learn to craft effective prompts to command AI models.
Integrate AI into your daily workflows ethically and effectively.
See how Google Cloud AutoML stacks up against similar alternatives in the market.
Explore these popular alternatives to Google Cloud AutoML for your specific needs.
Take your tool to the next level with Featured placements, Academy mentions with high-authority backlinks, 48h Fast‑Track listing, Newsletter features to thousands of AI practitioners, and exclusive Data/API access for growth insights.
Use this page as a starting point to evaluate Google Cloud AutoML alongside similar options. Our directory focuses on practical details that matter for adoption—capabilities, pricing signals, integrations, and real audiences—so you can shortlist with confidence and move from exploration to evaluation faster.
For a structured head‑to‑head, try the comparison view: Compare AI tools. To stay current with launches, model updates, and research breakthroughs, visit AI News. New to the space? Sharpen your understanding with AI Fundamentals.
Before adopting any tool, model your total cost at expected usage, verify integration coverage and API quality, and review privacy, security, and compliance. A short pilot on a real workflow will reveal reliability and fit quickly. Bookmark this site to track updates to Google Cloud AutoML and the broader ecosystem over time.
Found incorrect information or have concerns about Google Cloud AutoML? Let us know.
Looking for alternatives to Google Cloud AutoML or similar tools? Use our AI-powered chatbot to discover the perfect solution for your needs.