--- title: Google Cloud AutoML Reviews meta_title: 'Google Cloud AutoML Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 49 reviews by the users' company size, role or industry to find out how Google Cloud AutoML works for a business like yours. aggregate_rating: rating_value: 4.3 review_count: 49 scale: '5' date_modified: '2026-09-30' parent_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # Google Cloud AutoML Reviews **Vendor:** Google **Category:** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) **Average Rating:** 4.3/5.0 **Total Reviews:** 49 **AI Verified:** At least 10 G2 reviewers have confirmed using this product's AI features and functionality. ## About Google Cloud AutoML Google Cloud AutoML is a suite of machine learning products designed to enable developers with limited expertise to train high-quality custom models tailored to their specific business needs. By leveraging Google's advanced transfer learning and neural architecture search technologies, AutoML simplifies the process of building, deploying, and scaling machine learning models, making AI more accessible to a broader audience. Key Features and Functionality: - Automated Model Training: AutoML automates the selection of model architecture and hyperparameter tuning, reducing the need for manual intervention and specialized knowledge. - User-Friendly Interface: The platform offers an intuitive graphical interface that allows users to upload data, train models, and manage deployments with ease. - Versatile Model Types: AutoML supports various data types and tasks through specialized services: - AutoML Vision: For image classification and object detection. - AutoML Natural Language: For text classification, sentiment analysis, and entity recognition. - AutoML Translation: For creating custom translation models between language pairs. - AutoML Video Intelligence: For video classification and object tracking. - AutoML Tables: For structured data tasks like regression and classification. - Seamless Integration: AutoML integrates with other Google Cloud services, facilitating efficient data management, model deployment, and scalability. Primary Value and Problem Solving: Google Cloud AutoML democratizes machine learning by enabling users without deep technical expertise to develop and deploy custom models. This accessibility allows businesses to harness the power of AI to solve complex problems, such as improving customer experiences through personalized recommendations, automating content moderation, enhancing language translation services, and gaining insights from large datasets. By reducing the barriers to entry, AutoML empowers organizations to innovate and stay competitive in their respective industries. ## Google Cloud AutoML Pros & Cons Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews. **What users like:** - Users appreciate the **seamless AI integration** of Google Cloud AutoML, enhancing productivity without needing deep ML knowledge. (1 reviews) - Users appreciate the **ease of use** of Google Cloud AutoML, enabling quick training of models without deep expertise. (1 reviews) - Users appreciate the **easy integrations** of Google Cloud AutoML, enhancing their machine learning experience effortlessly. (1 reviews) - Users appreciate the **seamless integration** of Google Cloud AutoML, enhancing usability and collaboration with other Google services. (1 reviews) - Users appreciate the **intuitive interface** of Google Cloud AutoML, making machine learning accessible without deep expertise. (1 reviews) - Machine Learning (1 reviews) - User Interface (1 reviews) **What users dislike:** - Users find the **cost prohibitive** for smaller projects or students, making it less accessible for them. (1 reviews) - The **pricing can be expensive** for small projects or students, limiting accessibility and usage for some users. (1 reviews) ## Google Cloud AutoML Reviews ### 1. Good automation for faster machine learning workflows **Rating:** 4.5/5.0 stars **Reviewed by:** Shiv K. | Maintenance Engineer, Manufacturing, Mid-Market (51-1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 29, 2026 **Describe the project or task Google Cloud AutoML helped with:** Google Cloud AutoML offers a suite of machine learning products that enable developers with limited ML expertise to train high-quality models specific to their business needs. By leveraging Google's state-of-the-art transfer learning and neural architecture search technologies, AutoML simplifies the process of building custom models. It provides a user-friendly interface for data preparation, model training, and evaluation, making it accessible to a broader audience. The service integrates seamlessly with other Google Cloud services, ensuring a cohesive workflow from data ingestion to model deployment. **What do you like best about Google Cloud AutoML?** What I like most about Google Cloud AutoML is how it simplifies model training without requiring a lot of manual coding. The UI is straightforward, and its integration with other Google Cloud services makes it easier to manage data and deploy models. Training performance has been solid for quickly testing different models, and the automation saves time throughout development. It can deliver good ROI for teams that want to build ML solutions faster, although pricing still depends on usage. Onboarding and the Google Cloud documentation are helpful, and for my workflow the biggest advantages are the automated model selection and training. **What do you dislike about Google Cloud AutoML?** What I dislike about Google Cloud AutoML is that parts of the UI can feel confusing when you’re setting up models for the first time. The integrations are useful, but configuring data sources and permissions can still take a while and isn’t always as straightforward as I’d like. Training costs can also climb quickly with larger datasets, which can impact ROI. Overall performance is generally good, but training times can vary depending on the workload and how much data is involved. Better onboarding, clearer pricing estimates up front, and more step-by-step guidance during model setup would make the whole experience easier and less time-consuming. **Recommendations to others considering Google Cloud AutoML:** To improve the experience with Google Cloud AutoML, I recommend enhancing the UI to make it more intuitive, especially for first-time users. Providing clearer guidance on setting up data sources and permissions would be beneficial. Additionally, offering more transparent pricing information and detailed onboarding processes could help users better plan their projects. Finally, implementing more comprehensive step-by-step tutorials for model setup would greatly enhance user satisfaction. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Before we started using Google Cloud AutoML, we spent a lot of time manually preparing models, setting up the environment, testing different approaches, and managing experiments ourselves. AutoML has significantly reduced that workload by automating model training and making experimentation much easier through its straightforward UI. The integration with other Google Cloud services also helps keep the workflow smooth and connected, and the model performance has been solid for our use cases. Overall, it has helped us save development time and cut down on repetitive manual work, which has improved our ROI. The documentation and onboarding support have also made it simpler to get started and move forward with AI solutions. ### 2. Google Cloud AutoML Makes Building and Deploying ML Models Easy **Rating:** 4.5/5.0 stars **Reviewed by:** Subhashree S. | Developer, Computer Software, Enterprise (> 1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **G2 Icon:** Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise. **Reviewed Date:** August 10, 2026 **What do you like best about Google Cloud AutoML?** What I like best about Google Cloud AutoML is that it makes it much easier to build and deploy machine learning models without having to handle every part of the ML pipeline manually. The interface is fairly straightforward, and it’s useful for quickly testing models and getting a baseline without needing to be an expert in model development. It also fits well with other Google Cloud services, which makes it easier to use in existing cloud workflows. **What do you dislike about Google Cloud AutoML?** The main thing I dislike is that AutoML can feel a bit limiting when you need more control over the model or want to customize the training process. Some of the advanced options are not as flexible as building and training a model yourself. It can also become relatively expensive when running larger datasets or multiple training experiments. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Google Cloud AutoML helps us reduce the amount of time and effort needed to build and test machine learning models. We can get models trained and evaluated without having to manage the entire ML pipeline from scratch, which is especially useful for quick prototypes and smaller ML use cases. It helps us get experiments into a usable state faster and lets the team focus more on the actual business problem rather than infrastructure and model setup. ### 3. Google Cloud AutoML: Easy Custom Models with Strong Accuracy and Smooth GCP Integration **Rating:** 4.5/5.0 stars **Reviewed by:** Muhammed A. | Technical Project Manager , Logistics and Supply Chain, Mid-Market (51-1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal incentive as thanks for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal incentive as thanks for completing this review. **G2 Icon:** Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise. **Reviewed Date:** August 06, 2026 **What do you like best about Google Cloud AutoML?** Google Cloud AutoML has made it possible to build custom machine learning models tailored to our specific needs, like extracting data from KYC documents and classifying customer complaints, without needing deep ML expertise on the team. The interface for labeling training data and evaluating model performance is clean and accessible enough that the team could iterate without a dedicated data science background. Integration with the rest of our Google Cloud stack was smooth, connecting naturally with Cloud Storage and our backend without extra middleware. Performance has been solid for our production use cases once models were properly trained, handling both document extraction and text classification reliably. Pricing has offered reasonable ROI given the manual work it's automated, and onboarding didn't require extensive setup beyond gathering and labeling initial training data. Being able to train custom models rather than relying on generic pre-trained ones has noticeably improved accuracy for our domain-specific and Arabic-language use cases, which is the core value AutoML has delivered for us. **What do you dislike about Google Cloud AutoML?** Training a reliable custom model requires a fair amount of labeled data and iteration upfront, which takes real time investment before results are good enough for production use. Integrations with tools outside the Google Cloud ecosystem aren't as seamless, sometimes requiring custom glue code. Support response times for more nuanced training configuration questions were slower than expected during initial setup. Pricing for both training and ongoing predictions can add up quickly at higher volumes, and performance for edge cases with unusual document layouts or ambiguous complaint phrasing still requires manual review rather than fully automated handling. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Google Cloud AutoML has automated significant portions of manual work across our platform, from extracting structured data out of KYC documents to classifying incoming customer complaints, without requiring us to build and train models from scratch using raw ML frameworks. This has sped up processes like driver onboarding and complaint routing considerably, reducing the manual workload on our KYC review and support teams. ### 4. Google Cloud AutoML: Easy Custom ML Models Without Advanced Coding **Rating:** 5.0/5.0 stars **Reviewed by:** Harshwardhan B. | CEO, Information Technology and Services, Small-Business (50 or fewer emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** September 01, 2026 **What do you like best about Google Cloud AutoML?** Google Cloud AutoML made me build and deploy custom machine learning models without advanced programming or deep learning expertise. I know AI and ML, but when coding them, I have zero knowledge on that, this one definitely helped me on my ML journey. **What do you dislike about Google Cloud AutoML?** The cost, Its quite high. I mean it does give us accessibility of creating ML codes, like the convenience but when I used it, I had cloud credits so it was affordable, but for a consumer it would be a little on a expensive side. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Well, in my game design. It has helped me in rapid prototyping, I am able to get to make prototypes faster and show it to publishers rather than it used to take a lot of time. ### 5. Powerful AI Capabilities with Easy Cloud Integration **Rating:** 4.5/5.0 stars **Reviewed by:** Ashish B. | Operations Associate, Small-Business (50 or fewer emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **G2 Icon:** Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise. **Reviewed Date:** August 22, 2026 At G2, we prefer fresh reviews and we like to follow up with reviewers. They may not have updated their review text, but have updated their review. **Describe the project or task Google Cloud AutoML helped with:** Google Cloud AutoML offers a suite of machine learning products that enable developers to train high-quality models with minimal effort and expertise. It provides tools for image, video, text, and tabular data, allowing users to leverage Google's advanced machine learning technology without needing to write extensive code. The platform is designed to be user-friendly, making it accessible to both beginners and experienced developers. **What do you like best about Google Cloud AutoML?** What I like best about Google Cloud AutoML is how it combines strong AI capabilities with a relatively straightforward user experience. It integrates well with the broader Google Cloud ecosystem and performs reliably when training and evaluating models. The automation reduces development time and manual effort, which provides good ROI. The documentation and onboarding resources also make it easier to get started and move from experimentation to practical use. **What do you dislike about Google Cloud AutoML?** One drawback is that Google Cloud AutoML can feel somewhat complex for beginners, particularly when you’re trying to navigate the broader Google Cloud ecosystem at the same time. Costs can also add up quickly at higher usage levels, and the customization options may feel limited compared with building and tuning models manually. **Recommendations to others considering Google Cloud AutoML:** To make the most of Google Cloud AutoML, it's recommended to start with a clear understanding of your project goals and the specific machine learning tasks you want to automate. Familiarize yourself with the Google Cloud ecosystem to better navigate its features and services. Consider starting with smaller projects to get accustomed to the platform before scaling up. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Google Cloud AutoML helps reduce the time and technical effort required to build and deploy machine learning models. It lets us automate key parts of the model development process, try out different approaches quickly, and still get useful results without needing deep ML expertise. As a result, we can work more efficiently, speed up experimentation, and keep the team focused on business use cases instead of getting bogged down in the technical complexity of building models from scratch. ### 6. Streamlined MLOps and rapid prototyping for production vision pipeline **Rating:** 5.0/5.0 stars **Reviewed by:** Vikas s. | Senior Machine Learning Engineer, Information Technology and Services, Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 29, 2026 **What do you like best about Google Cloud AutoML?** Reducing the lead time from initial research to a live production endpoint is a constant challenge for engineering teams. Google Cloud AutoML, particularly the Vision module within Vertex AI, entirely automates the traditionally tedious stages of hyperparameter tuning and neural architecture search. When building a recent face recognition attendance application, skipping manual OpenCV cascade tuning and relying on Vertex AI's automated transfer learning allowed for rapid baseline generation. The most significant advantage is its native integration with MLOps workflows. After training, deploying a highly available REST prediction endpoint takes just a few clicks within the Google Cloud console. Hooking this autoscaling endpoint directly into a Python Flask backend is straightforward, shifting the team's focus away from managing model-serving infrastructure and toward core application logic. **What do you dislike about Google Cloud AutoML?** The high level of abstraction creates a rigid environment for complex modeling scenarios. Because the AutoML pipeline operates largely as a black box, fine-tuning specific custom loss functions, adjusting hidden network layers, or debugging gradient issues on edge cases is nearly impossible. If a model hits a performance ceiling on an imbalanced dataset, the only real solution is to abandon the AutoML interface and rewrite the training pipeline from scratch using a custom TensorFlow or PyTorch environment. Additionally, the compute costs associated with training massive image datasets can escalate rapidly if node-hour budgets are left uncapped during extensive model iterations. **What problems is Google Cloud AutoML solving and how is that benefiting you?** The platform fundamentally solves the infrastructure bottleneck associated with rapid prototyping. It completely removes the need to manually provision GPU clusters, configure Docker containers, or manage complex CI/CD deployment pipelines just to test a hypothesis. By drastically reducing the time-to-first-model, engineering teams can quickly validate whether a new dataset contains actionable predictive value before committing weeks of development time to a fully custom-coded machine learning architecture. ### 7. Speeds up vision models, but watch out for the training costs **Rating:** 5.0/5.0 stars **Reviewed by:** Sachin G. | Machine Learning Engineer, Information Technology and Services, Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 25, 2026 **What do you like best about Google Cloud AutoML?** I’ve been doing a lot of work with computer vision pipelines recently, specifically building out a face recognition system for automated attendance tracking. What I appreciate most about Cloud AutoML (specifically the Vision product) is how incredibly fast it lets me go from a folder of labeled images to a working REST endpoint. I typically build my application backends using Python and Flask, and dropping the Google Cloud client library into my Flask routes to call the AutoML endpoint is super straightforward. It handles all the complex transfer learning and hyperparameter tuning under the hood. Instead of spending weeks manually tweaking OpenCV scripts or custom neural nets, I get a highly accurate model just by supplying good training data. **What do you dislike about Google Cloud AutoML?** The pricing can get out of hand very quickly, especially the hourly compute costs for training larger vision datasets. You really have to keep an eye on your node hours. Also, while the cloud-hosted prediction API is great, exporting the models to run completely offline (like Edge TPU or TF Lite) can be surprisingly finicky. The UI abstracts so much away that when an edge export fails, figuring out the exact compatibility issue in the logs takes more digging than it should. **What problems is Google Cloud AutoML solving and how is that benefiting you?** It completely eliminates the infrastructure bottleneck during the prototyping phase. I don’t have to provision GPUs or manage training scripts manually. It lets me focus purely on the application logic and data quality, knowing that the platform will automatically find the best model architecture for my specific image dataset. It turns what used to be a month-long machine learning project into a few days of work. ### 8. Easy way to get started with machine learning **Rating:** 4.5/5.0 stars **Reviewed by:** Dr S. | Doctor, Small-Business (50 or fewer emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 13, 2026 **What do you like best about Google Cloud AutoML?** What I like most is that AutoML makes machine learning feel much less complicated,It handles a lot of the technical work in the background,so I can focus more on the data and the actual problem I’m trying to solv e it’s also convenient for getting a model up and running without spending too much time building everything from scratch **What do you dislike about Google Cloud AutoML?** The main thing I dislike is that it can feel a bit overwhelming when you first start using it, especially if you’re not already familiar with Google Cloud. Some of the settings and options take time to understand. I’d also like to have a little more flexibility and control over certain parts of the model-building process. **What problems is Google Cloud AutoML solving and how is that benefiting you?** The main problem it solves is the complexity of building and training machine learning models from scratch. It saves time by automating a lot of the model development process, which means I don’t have to spend as much time on technical setup and can focus more on the actual data and problem. It’s particularly helpful when I want to test an ML idea quickly and see whether it can work in practice. ### 9. Faster ML Model Development by Google **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** July 10, 2026 **What do you like best about Google Cloud AutoML?** What I liked best was how well it fit into our existing Google cloud env. We used it to build image classification models much fatsre than our traditional ML workflows, which reduced the time from data collection to deployment. The model training and deployment process is mostly automated, so our team could spend more time improving data quality instead of writing training code. I also liked the prediction API because it was easy to integrate with our internal applications. It's best part is how we quickly test different datasets and compare model performance without setting up seprate infrastructure. It definitely helped use deliver AI features to the business faster. **What do you dislike about Google Cloud AutoML?** The biggest downside for us was the pricing, especially when running multiple training experiemnts because the cost can increase quickly. I also felt there should be more control over advanced model tuning for teams that want to customize beyond the default settings. The error message during failed training jobs were sometimes not detailed enough, so troubleshooting took longer than expected. **What problems is Google Cloud AutoML solving and how is that benefiting you?** So before using google cloud AutoML building ML models required data scientists and a lot of development time. But with AutoML our team was able to create and deploy custom models much faster and even for business teams with limited ML expertise. It also helped us automate document and image classifications which reduced manual work and improved accuracy. The faster deployment cycle also meant we could validate new ideas quickly and deliver AI-powered feature to our users in much less time. ### 10. Google Cloud AutoML: Easy, Fast Model Building with Minimal Coding **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Manufacturing | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 21, 2026 **What do you like best about Google Cloud AutoML?** Google Cloud AutoML makes it easy to build and test machine learning models without needing deep ML expertise. I especially like the simple workflow and reduced coding effort, which makes it much faster to test ideas and get models up and running. **What do you dislike about Google Cloud AutoML?** I think the main downside is that it can feel a little limiting when you want more control over the model. Some settings and results are also not very clear at first, so there can still be a learning curve. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Google Cloud AutoML helps us test machine learning ideas without spending too much time building everything from scratch. It makes the process faster and allows us to see whether a use case is worth investing more time in. ### 11. Easy to Use, Minimal Coding, and Smooth Google Integration **Rating:** 4.5/5.0 stars **Reviewed by:** Siddhant D. | Application Engineer, Mechanical or Industrial Engineering, Mid-Market (51-1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 31, 2026 **What do you like best about Google Cloud AutoML?** this platform is very easy to use, it gives us tools for model or data preparation, it also easy to integrate with other google services, minimal coding required **What do you dislike about Google Cloud AutoML?** if data sheet is large then its expensive, also model training is depends on data as it takes time, require machine learning concept clear before using it **What problems is Google Cloud AutoML solving and how is that benefiting you?** it supports our automation of data analysis, reduce time to develop model & training, also this platform supports ai, ### 12. A great tool for quick prototyping without heavy coding **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Apparel & Fashion | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 27, 2026 **What do you like best about Google Cloud AutoML?** I really love how simple Google Cloud AutoML makes the whole machine learning process. You don't need to be a hardcore data scientist or coding expert to build good models. Uploading clean data, tagging images or text, and training the model happens seamlessly in just a few clicks. The best part is that it handles the complex infrastructure behind the scenes, and the accuracy we get through transfer learning is surprisingly high. It also connects perfectly with Google Cloud Storage and BigQuery, which cuts down a lot of manual data moving work. For launching quick prototypes, it is an absolute lifesaver. **What do you dislike about Google Cloud AutoML?** The biggest downside is definitely the cost, as it can get incredibly expensive very quickly. For smaller projects or startups, the training and hosting fees are quite high compared to running custom models on local servers. Another issue is the "black box" nature of the tool. Since everything is automated, you don't get much control or visibility into why a specific model is behaving a certain way, making deep debugging frustrating. The documentation can also be a bit chaotic and hard to navigate when you run into specific errors. Lastly, importing and preparing heavy datasets within the web UI sometimes feels sluggish and throws random timeout errors. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Google Cloud AutoML primarily solves the problem of talent and resource shortage when it comes to building machine learning models. We don't have a large team of dedicated data scientists, so doing everything manually from scratch was never an option for us. It helps us quickly build custom classification tools and text analyzers without waiting for weeks of development. The main benefit we get is speed-to-market. We can test an idea, train a model on our specific business data, and see if it works within a few days. It takes away all the headache of setting up servers, managing GPUs, or writing complex deep learning frameworks, allowing our small team to focus on the actual business logic. ### 13. Build High-Quality ML Models Fast with Minimal Coding on Google Cloud **Rating:** 4.5/5.0 stars **Reviewed by:** Ajit M. | IT Administrator, Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through Google One Tap using a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 28, 2026 At G2, we prefer fresh reviews and we like to follow up with reviewers. They may not have updated their review text, but have updated their review. **What do you like best about Google Cloud AutoML?** It allows users to build and train high-quality ML models with minimal coding, while still benefiting from Google's powerful cloud infrastructure. **What do you dislike about Google Cloud AutoML?** It offers limited customization compared to building machine learning models from scratch. It can also become expensive when working with large datasets or running extensive training. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Google Cloud AutoML solves the problem of building machine learning models without requiring deep expertise in coding or data science. It automates much of the model training and evaluation process, making AI more accessible and faster to implement. This benefits me by saving time, reducing the complexity of machine learning projects, and helping me create and deploy models more efficiently. ### 14. Easy to Use Yet Customizable, with Room to Grow into Vertex AI **Rating:** 4.5/5.0 stars **Reviewed by:** Nikhil M. | Statistical Programmer, Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** July 08, 2026 **What do you like best about Google Cloud AutoML?** The feature many organizations appreciate most is the balance between ease of use and customization. Beginners can quickly create useful models, while experienced practitioners can move to more advanced Vertex AI capabilities when they need greater control over training, deployment, or optimization. **What do you dislike about Google Cloud AutoML?** In practice, the biggest complaint from advanced ML teams is usually the trade-off between convenience and control. AutoML excels at accelerating development and creating strong baseline models, but experts often outgrow it when they need deep customization, explainability, or cost optimization. **What problems is Google Cloud AutoML solving and how is that benefiting you?** So the core value of Google Cloud AutoML is that it helps organizations build and deploy machine learning solutions faster, with less specialized expertise and infrastructure management, enabling them to focus more on business outcomes than on the complexities of machine learning itself.Provide your feedback on BizChat ### 15. Very Easy to Use, Minimal Coding for Formatted Results **Rating:** 5.0/5.0 stars **Reviewed by:** Arpit S. | Customer Success Associate, Information Technology and Services, Mid-Market (51-1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through Google using a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **G2 Icon:** Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise. **Reviewed Date:** July 28, 2026 **What do you like best about Google Cloud AutoML?** It is very easy to use you can perform easily command and get it formated as you command with minimal coding you can us this. **What do you dislike about Google Cloud AutoML?** As much I have used it is very simple to use only the major drawback I have faced with the Pricing which is too high as you need to scale at large level. **What problems is Google Cloud AutoML solving and how is that benefiting you?** If you are a new user you can easily use and make a code using this and train your model very easily. ### 16. Accurate Fraud Detection and Easy Integration with Cloud AutoML **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 04, 2026 **What do you like best about Google Cloud AutoML?** In Cloud AutoML the best thing is it detects the fraud and create suggested image and detect the language text globally with accurate rate, The UI is very easy and user friendly and you can easily integrate the software with other google Apps very smoothly and onboarding process is also very **What do you dislike about Google Cloud AutoML?** It's slightly expensive if compare from other software, but yes the functionality which this software provides is irreplaceable **What problems is Google Cloud AutoML solving and how is that benefiting you?** It detects and read the algorithm accurately without any discrepancy and provide many features which detects video call, audio call, AI and models for processing the development and provide the transparency. It's very easy to integrate with other tools and software as well ### 17. User-Friendly AutoML That Speeds Up Building and Deploying ML Models **Rating:** 5.0/5.0 stars **Reviewed by:** Anjan S. | Public Health Intern, Hospital & Health Care, Enterprise (> 1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** July 27, 2026 **What do you like best about Google Cloud AutoML?** Google Cloud AutoML is user-friendly and makes it easy to build and deploy machine learning models with minimal coding. It saves time and accelerates the delivery of AI solutions. **What do you dislike about Google Cloud AutoML?** The pricing is a bit high for small businesses, and the advanced configurations can be challenging for new users without sufficient guidance. **What problems is Google Cloud AutoML solving and how is that benefiting you?** It automates the creation of machine learning models without requiring deep AI expertise, saving significant time while improving the accuracy and efficiency of our workflows. ### 18. Easy, Low-Code ML Builds and Deployments That Save Time **Rating:** 4.0/5.0 stars **Reviewed by:** Raju S. | Senior Business Analyst, Information Technology and Services, Mid-Market (51-1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through Google using a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** July 21, 2026 **What do you like best about Google Cloud AutoML?** Its easy to use and it helps in build and deploy machine learning models with minimal coding. It usually saves the time while deliver the accurate AI Solutions. **What do you dislike about Google Cloud AutoML?** The pricing is high for small businesses and advanced configuration require for new users so they can learn more. **What problems is Google Cloud AutoML solving and how is that benefiting you?** It helps in automating machine learning model creation without need of deep AI expert and saves alot time and improves the accuracy for our workflows. ### 19. Clear Dashboards and Drag-and-Drop Tools Make Model Training Easy **Rating:** 4.5/5.0 stars **Reviewed by:** BINAYAK B. | Procurement Executive, Enterprise (> 1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** September 23, 2026 **What do you like best about Google Cloud AutoML?** The platform uses clear dashboards and drag-and-drop tools to handle data labeling and training. **What do you dislike about Google Cloud AutoML?** Costs rise quickly as data volume, training hours, storage, and prediction requests increase. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Eliminates the need for deep data science knowledge to build high-quality models. ### 20. Google Cloud AutoML Makes Model Training Easy **Rating:** 5.0/5.0 stars **Reviewed by:** Mohit M. | Owner, Small-Business (50 or fewer emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** September 02, 2026 **What do you like best about Google Cloud AutoML?** I like Google cloud Auto ML, because it simplifies machine learning automated model training is reducing the need for extensive coding **What do you dislike about Google Cloud AutoML?** The main drawback is that it can be expensive and offers less flexibility for users who need advanced customisation and control over their models **What problems is Google Cloud AutoML solving and how is that benefiting you?** Well, cloud Auto ML reduces the complexity of building machine, learning models, helping me to save time and get accurate results with minimal coding ### 21. Auto Model Selection Makes Projects Effortless **Rating:** 5.0/5.0 stars **Reviewed by:** Tulsi L. | Practice Lead - Data Science & Engineering, Mid-Market (51-1000 emp.) **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** July 29, 2026 **What do you like best about Google Cloud AutoML?** I like the auto model selection for the projects **What do you dislike about Google Cloud AutoML?** The increase in costs with heavy training data becomes a concern **What problems is Google Cloud AutoML solving and how is that benefiting you?** I think the time cost of training model and tuning them is something to consider, its a huge benefit when comes to time limitations on projects ### 22. Easy Google Cloud Integration That Speeds Up Image Classification with AutoML **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Staffing and Recruiting | Mid-Market (51-1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** July 23, 2026 **What do you like best about Google Cloud AutoML?** One of my friend using this software, as per my knowledge it is very easy to integrate with Google cloud environment. It sped up image classification model development through automated training and deployment, letting us focus on data quality. The API predication was simple to integrate, and testing different datasets and comparing model performance was quick without extra infrastructure. **What do you dislike about Google Cloud AutoML?** One common concern among experienced ML teams is balancing ease of use with flexibility. While AutoML is great for speeding up development and building reliable baseline models it can become limiting when projects require advanced customization. **What problems is Google Cloud AutoML solving and how is that benefiting you?** It helps build machine learning models quickly without extension AI knowledge, saving time and enhancing accuracy of our workflows. ### 23. Easy, Scalable ML Model Building and Deployment with Minimal Coding **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 29, 2026 **What do you like best about Google Cloud AutoML?** It makes it easy to build and deploy ML models with little coding and at the same time it still offers strong scalability. **What do you dislike about Google Cloud AutoML?** The main problem is that it can get costly when use it a lot and it gives less options and less power compared to creating models on your own. **What problems is Google Cloud AutoML solving and how is that benefiting you?** It makes building ML models simpler saving time during development. It also helps me in testing and deploying solutions easily. Best part is no need for the expertise in ML ### 24. Easier Than Most, But Pricing Feels High for a Commoditized Tool **Rating:** 3.5/5.0 stars **Reviewed by:** Damien P. | Managing Director, Small-Business (50 or fewer emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 27, 2026 At G2, we prefer fresh reviews and we like to follow up with reviewers. They may not have updated their review text, but have updated their review. **What do you like best about Google Cloud AutoML?** easier than most other products but not as easy as claude **What do you dislike about Google Cloud AutoML?** Pricing is higher than what we would expect from commoditised **What problems is Google Cloud AutoML solving and how is that benefiting you?** not solving any but does save some time when looking for data sets ### 25. Great for Importing Google Cloud Datasets, but Fraud Detection Needs Improvement **Rating:** 3.0/5.0 stars **Reviewed by:** Tierra J. | Supervisor, Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through Google using a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 27, 2026 **What do you like best about Google Cloud AutoML?** Import and organize large datasets stored in Google Cloud. **What do you dislike about Google Cloud AutoML?** Some time the fraud detection isn’t accurate **What problems is Google Cloud AutoML solving and how is that benefiting you?** Monitor, retrain, version, and manage models across their entire lifecycle. ### 26. Fast Prototyping and Easy Model Training, but Cloud Costs Can Add Up **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Higher Education | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 13, 2026 **What do you like best about Google Cloud AutoML?** Speeds up prototyping and adjusts quick baseline models. Allows users without big data science skills to train the new models. Connects smoothly with Google Cloud storage, BigQuery **What do you dislike about Google Cloud AutoML?** raining and running large-scale jobs on the cloud can get expensive fast. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Delivers high accuracy for standard image, text, and translation tasks. ### 27. Easy-to-Use Interface That Cuts ML Development Effort **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Printing | Enterprise (> 1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 08, 2026 **What do you like best about Google Cloud AutoML?** Easy-to-use interface and significantly reduces the ML development effort **What do you dislike about Google Cloud AutoML?** Can become expensive at scale, and advanced customization is limited compared with building models from scratch. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Makes machine learning more accessible by letting teams build and deploy custom ML models with minimal coding. ### 28. Fast and reliable AutoML platform for building ML model with case **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through LinkedIn **Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate. **Reviewed Date:** September 10, 2025 **What do you like best about Google Cloud AutoML?** Google Cloud AutoML makes it very easy to train high-quality machine learning models without requiring deep ML expertise. The interface is intuitive, the documentation is clear, and the integration with other Google Cloud services is seamless. **What do you dislike about Google Cloud AutoML?** The pricing can be expensive for small projects or students **What problems is Google Cloud AutoML solving and how is that benefiting you?** It saves me a lot of time. I don't have to code everything from scratch, I can just focus on the data and get a working model quickly. ### 29. Google Cloud AutoML: Powerful performance and efficient ML kit **Rating:** 4.5/5.0 stars **Reviewed by:** Ravi P. | Machine Learning Engineer, Information Technology and Services, Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** August 17, 2019 **What do you like best about Google Cloud AutoML?** Google AutoML kit is one of the best platforms for developers of Machine Learning, as the main benefit is that it is from Google and ML is highly affected by Google. In that manner, Google's AutoML kit provides very sophisticated ML techniques and algorithms support. In addition to that, the performance and accuracy of AutoML algorithms are way better than other ML platforms. Create and train the model of any specific problems is very easy and fast. Google AutoML Algorithms and techniques can easily handle large and complex data processing and as is it on the cloud, I get extremely good GPU support that would rather cost me thousands of bucks. It really makes the difference in how I develop ML applications. **What do you dislike about Google Cloud AutoML?** One thing I believe can be improved that Google can get know regarding my private data sets which sometimes can be a privacy issue for some users. So, Google may introduce some private data loading techniques on AutoMl platform. Other than that there are not any major issues in it. **Recommendations to others considering Google Cloud AutoML:** Google Could AutoML is a very cost-effective solution in terms of hardware resources. Also, with that, you will get security as well as reliable performance for any kind of complex data you want to process. Definitely anyone who is working in ML should go with it once. **What problems is Google Cloud AutoML solving and how is that benefiting you?** I use Google Could AutoML for various purposes such as data preprocessing, dataset manipulation and mainly for model training. We have monthly subscription based plan for Google AutoML platform at our company and as a machine learning developer, I am utilizing it for developing a different pilot application for demo purpose as well as main projects of ML in it. ### 30. A safe and easy place **Rating:** 4.0/5.0 stars **Reviewed by:** Roberto H. | Full stack, Enterprise (> 1000 emp.) **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **AI Translated:** This review has been translated from English using AI. **Reviewed Date:** July 26, 2019 **What do you like best about Google Cloud AutoML?** This helped our company improve decision-making more quickly and easily. Faced with a set of data of interest, AutoML extracts the dataset of interest from users and determines a high-performance network architecture. It's the quick and easy way to get started quickly and obtain sophisticated models later. Ease of use and the ability to hire interns to tag photos so the senior team can focus on the technology. **What do you dislike about Google Cloud AutoML?** There is still a lot of art associated with training machine learning models. It's difficult for us to debug bad image matches. Every now and then, the beta has a flaw that I can't remove from my model. **What problems is Google Cloud AutoML solving and how is that benefiting you?** I was trying to build an image recognition app at a Hackathon. We are modernizing a laser marking system to use image recognition, and we created an app when it was in alpha for a client to detect their hinges. Backing up data and storage is very necessary. ### 31. Great Training Tool **Rating:** 3.5/5.0 stars **Reviewed by:** Edynn S. | Executive Director , Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** November 01, 2018 **What do you like best about Google Cloud AutoML?** You can use Google’s human labeling service to have real-life people annotate or clean your labels to make sure your models are being trained on high-quality data. It helps to make sure your data is clean and your organization can run smoother. It has a simple interface. **What do you dislike about Google Cloud AutoML?** it has an amazing UI and provides a great interface but it is not the cheapest option out there. Especially if you need custom training the price can be pretty hefty. **Recommendations to others considering Google Cloud AutoML:** They provide integration with human labeling which is great for smaller companies to have access to a much larger data base and technology. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Cloud AutoML is fully integrated with other Google Cloud services, providing a method of access across the entire Google Cloud service line. We are able training data in Cloud Storage. To generate a prediction on your trained model, simply use the existing Vision API by adding a parameter for your custom model or use Cloud ML Engine's online prediction service. ### 32. Makes creating machine learning models easier **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Military | Mid-Market (51-1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Source: G2 Gives Campaign:** G2 Gives Campaign. The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Reviewed Date:** April 08, 2019 **What do you like best about Google Cloud AutoML?** The tool has facilitated the creation of machine learning models that we use in other applications. **What do you dislike about Google Cloud AutoML?** There is still a lot of art associated with training machine learning models. Some scaffolding to help with how to tune models would be helpful. **What problems is Google Cloud AutoML solving and how is that benefiting you?** We improved the accuracy of our machine learning in an important application. We were shooting for 99.9% accuracy. Our raw ML model got us to 90%, and with some pre- and post-processing of the data, we were able to get close to 99%. ### 33. using cloud auto ml as a building block for complicated computer vision problems **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Oil & Energy | Enterprise (> 1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Source: G2 Gives Campaign:** G2 Gives Campaign. The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Reviewed Date:** April 07, 2019 **What do you like best about Google Cloud AutoML?** using cloud auto ml as a building block for complicated computer vision problems. How quickly it trains, clearly doing a great implementation of transfer learning. **What do you dislike about Google Cloud AutoML?** that i cannot take my model out. That i am tied to making predictions through the api of this service. There is no clear upfront description of data ownership, is google reserving the right to look at my training data for future model building? **What problems is Google Cloud AutoML solving and how is that benefiting you?** many problems related to earth sub-surface characterization. ### 34. AutoML for Automated Architecture Search **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** This review contains authentic analysis and has been reviewed by our team **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** October 26, 2018 **What do you like best about Google Cloud AutoML?** Google's AutoML minimizes the hand-tuning of the hyper-parameters of machine learning algorithm, such as neural networks, deep networks, to near zero. Given a dataset of interest, AutoML takes the dataset of interest from the users and determines a high performing network architecture. **What do you dislike about Google Cloud AutoML?** Given that the AutoML is proprietary software from Google, it is kind of Blackbox to the users, while understandable, users from the same domain kind of benefit from the nuances of the AutoML to deduce more intuitive inferences from insights used by AutoML to determine the network architecture. **What problems is Google Cloud AutoML solving and how is that benefiting you?** AutoML has helped reduce the computational time and resources required to determine architectures for large datasets, such as ImageNet (ILSVR2015) which contains 1.25 million images of 220x320 resolution from real-world scenarios. With that being said, for a dataset of this magnitude, it is near impossible to hand tune effectively hyper-parameters. ### 35. great product **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Source: G2 Gives Campaign:** G2 Gives Campaign. The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Reviewed Date:** April 11, 2019 **What do you like best about Google Cloud AutoML?** Traditionally the major problem with ml apis have been that the services have been too generic for enterprise use. Automl enables us to finally use ml api services in an enterprise context by tailoring the results to the specific use case needs **What do you dislike about Google Cloud AutoML?** Would be good to have ml automl recommendation engine **What problems is Google Cloud AutoML solving and how is that benefiting you?** vision automl ### 36. AutoML for Image Recognition **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Defense & Space | Mid-Market (51-1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Source: G2 Gives Campaign:** G2 Gives Campaign. The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Reviewed Date:** April 08, 2019 **What do you like best about Google Cloud AutoML?** Ease of use and ability to hire interns to tag photos so senior staff can focus on tech. **What do you dislike about Google Cloud AutoML?** Hard for us to debug bad imagery matches. **Recommendations to others considering Google Cloud AutoML:** In our case of image recognition, we needed 10s of thousands of pictures. **What problems is Google Cloud AutoML solving and how is that benefiting you?** We are modernizing a laser tag system to instead use image recognition. ### 37. AutoML is the least amount of work to train your models **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Enterprise (> 1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Source: G2 Gives Campaign:** G2 Gives Campaign. The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Reviewed Date:** April 08, 2019 **What do you like best about Google Cloud AutoML?** It's the quick and easy way of up and running quickly and getting sophisticated models later on **What do you dislike about Google Cloud AutoML?** Additional modelling techniques can be added in the future. So you have what you have at a given point in time. Could be made dynamic. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Prototyping on some use cases. ### 38. AUTOML Vision **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Source: G2 Gives Campaign:** G2 Gives Campaign. The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Reviewed Date:** April 08, 2019 **What do you like best about Google Cloud AutoML?** I really like the easy way to make ML Models. Even for me as a CEO **What do you dislike about Google Cloud AutoML?** It is still in Beta and sometimes buggy. **What problems is Google Cloud AutoML solving and how is that benefiting you?** we build an app when it was in alpha for a customer to detect their hinges ### 39. Review of AutoML **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Pharmaceuticals | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Source: G2 Gives Campaign:** G2 Gives Campaign. The reviewer received either a gift card or a donation made to a charity of their choice in exchange for writing this review. **Reviewed Date:** April 11, 2019 **What do you like best about Google Cloud AutoML?** simple application for a non-ML experienced user **What do you dislike about Google Cloud AutoML?** There has been nothing found at this time **What problems is Google Cloud AutoML solving and how is that benefiting you?** category recognition - pharma docs
Benefits - decent confidence levels are derived after training the model with adequate examples ### 40. Love it! **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Education Management | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through LinkedIn **Source: Seller invite:** Invitation from a seller or affiliate. This reviewer was not provided any incentive by G2 for completing this review. **Reviewed Date:** October 17, 2018 **What do you like best about Google Cloud AutoML?** I find that this is tailored to my business's needs when it comes to automating photo identification and transferring systems. It feels really good to have my photos automated and classified efficiently. I'm so happy I get to outsource this issue. **What do you dislike about Google Cloud AutoML?** I sometimes find the translations to be a little off and they aren't always accurate or need more photos. I don't use it that often, so I can't speak more to what I don't like about it. **What problems is Google Cloud AutoML solving and how is that benefiting you?** I am automating photo identification and human identification, and it doesn't need that much information, which is great. The work is very quick and typically very accurate. This can help on a variety of issues in blogging and setting up systems. ### 41. powerful API to desktop user **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** October 17, 2018 **What do you like best about Google Cloud AutoML?** The vision and text API's were really easy to use, or train on custom datasets. very good tutorials and help available online and supportive community **What do you dislike about Google Cloud AutoML?** The late limits are little too small, even for students **Recommendations to others considering Google Cloud AutoML:** Easy to set up, if at a hackathon, would recommend using this service. **What problems is Google Cloud AutoML solving and how is that benefiting you?** I was trying to build a image recognition application at a Hackathon ### 42. overall good and user friendly **Rating:** 3.5/5.0 stars **Reviewed by:** Matias D. | Project Management Analyst, Enterprise (> 1000 emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** November 01, 2018 **What do you like best about Google Cloud AutoML?** It helped our company to enhance our decision making faster and easier. Also it reduced time to market. **What do you dislike about Google Cloud AutoML?** We ran into permissions/security issues but they aren't too hard tor resolve. **What problems is Google Cloud AutoML solving and how is that benefiting you?** Improve business process agility Improve business process outcomes Improve customer relations/service ### 43. A little difficult to use **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** November 01, 2018 **What do you like best about Google Cloud AutoML?** This software gets the job done. It is beneficial for newer protocols and analysis. **What do you dislike about Google Cloud AutoML?** It is not the easiest software to use and requires a lot of training. When starting a new project there are many things that determine the ease of use depending on the type of project and the complexity of analysis. **What problems is Google Cloud AutoML solving and how is that benefiting you?** The program allows to create customized models for the work that we've been doing/ ### 44. Fast and easy **Rating:** 4.0/5.0 stars **Reviewed by:** Mina S. | Senior Business Specialist, Financial Services, Mid-Market (51-1000 emp.) **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** October 31, 2018 **What do you like best about Google Cloud AutoML?** Fast and easy and secure mo service with high quality **What do you dislike about Google Cloud AutoML?** There is a lot of permission and security issues **What problems is Google Cloud AutoML solving and how is that benefiting you?** Great for machine learning for people without so many experiences ### 45. Great experience **Rating:** 4.0/5.0 stars **Reviewed by:** Stasiu S. | Owner, Small-Business (50 or fewer emp.) **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** October 17, 2018 **What do you like best about Google Cloud AutoML?** Very easy to use, I was able to pick it up and learn pretty quickly. **What do you dislike about Google Cloud AutoML?** Nothing really. Everynow and then the beta has a glitch **What problems is Google Cloud AutoML solving and how is that benefiting you?** Has really helped me to expand quicker. ### 46. A safe easy place **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Accounting | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** November 01, 2018 **What do you like best about Google Cloud AutoML?** The real time feature and the ability to connect with others **What do you dislike about Google Cloud AutoML?** It is still in the trial period so I have not come across anything that I don't like **What problems is Google Cloud AutoML solving and how is that benefiting you?** The ability to categorize who should see different emails, different requests, etc., Versus the company needing to figure out who should work on what and respond to ### 47. works well **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Online Media | Mid-Market (51-1000 emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** November 01, 2018 **What do you like best about Google Cloud AutoML?** I like the google sheets/docs. it is a great way to collaborate. **What do you dislike about Google Cloud AutoML?** google hangout is not as good as slack because you can't upload documents **What problems is Google Cloud AutoML solving and how is that benefiting you?** it helps us create documents and collaborate. ### 48. Google Cloud **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Entertainment | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through LinkedIn **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** October 17, 2018 **What do you like best about Google Cloud AutoML?** Google’s cloud implementation is top notch! **What do you dislike about Google Cloud AutoML?** A little buggy in some areas. Need to be ironed out. **What problems is Google Cloud AutoML solving and how is that benefiting you?** The benefits have been great. We can get products and information out to customers better than ever. ### 49. Very convenient **Rating:** 2.5/5.0 stars **Reviewed by:** Verified User in Consumer Goods | Small-Business (50 or fewer emp.) This reviewer's identity has been verified by our review moderation team. They have asked not to show their name, job title, or picture. **Validated Reviewer:** Validated through a business email account **Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review. **Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review. **Reviewed Date:** October 17, 2018 **What do you like best about Google Cloud AutoML?** Storage data, very convenient to use and easily accessible. Easy to learn the system **What do you dislike about Google Cloud AutoML?** There’s nothing to dislike but maybe slow **What problems is Google Cloud AutoML solving and how is that benefiting you?** Backing up data and storage that is much needed ## Google Cloud AutoML Discussions - [What is Google Cloud AutoML used for?](https://www.g2.com/discussions/what-is-google-cloud-automl-used-for) - [View Google Cloud AutoML pricing details and edition comparison](https://www.g2.com/products/google-cloud-automl/reviews?section=pricing&secure%5Bexpires_at%5D=2026-09-30+04%3A39%3A55+-0500&secure%5Bsession_id%5D=28b3f9e5-d1af-4515-bd66-ed8db00a5d0a&secure%5Btoken%5D=07b1f8f5666d8ac6666a05ea377abc822f9c0568b4d3a819dc34840844853d03&format=llm_user) ## Google Cloud AutoML Features **Additional Functionality** - Tagging - Natural Language Processing - Data Extraction - Multi-Language - Predictive Analytics - Drag & Drop - Speech Recognition - Reporting/Analytics - Data Storage Management - Virtual Personal Assistant (VPA) - AI Copilot - Customer Segmentation - Collaboration Tools - Data Import/Export - Generative AI - For eCommerce - Role-Based Permissions - Customizable Branding - Search/Filter - Monitoring - Document Management - API - Data Visualization - Trend Analysis - Machine Learning - Access Controls/Permissions - Alerts/Escalation - Performance Metrics - Real-Time Data - Third-Party Integrations - Mobile App - Multiple Data Sources - For Sales Teams/Organizations - Sentiment Analysis - Activity Dashboard - Chatbot - Workflow Automation **System** - Data Ingestion & Wrangling - Real-Time Data **Data Ingestion & Preparation - Low-Code Machine Learning Platforms** - Automatic Data Profiling & Quality Assessment - Multi‑Source Connector Support - Schema Drift / Change Detection **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training - Database Support - Multi-Language **Model Development** - Feature Engineering **Model Construction & Automation - Low-Code Machine Learning Platforms** - Guided Algorithm & Hyperparameter Recommendation - Code Extensibility - Automated Feature Engineering **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Deployment** - Managed Service - Application - Scalability **Additional Functionality** - Customizable Reports - Collaboration Tools - Data Extraction - Semantic Search - Data Storage Management - Ad hoc Reporting - Reporting/Analytics - Predictive Analytics - Activity Dashboard - Access Controls/Permissions - Visual Analytics - Data Mapping - Data Synchronization - Statistical Analysis - Categorization/Grouping - Trend Analysis - Data Profiling - Linked Data Management - Data Visualization - API - Multiple Data Sources - Sentiment Analysis - Search/Filter - Data Import/Export - Data Capture and Transfer - AI Copilot - Monitoring - Data Connectors - Ad hoc Analysis - Text Mining - Reporting & Statistics - Predictive Modeling - Real-Time Analytics - Configurable Workflow - Tagging - Endpoint Management - No-Code - Data Preparation - Auditing - Big Data Analytics - ML Algorithm Library - Data Management - Activity Tracking - Data Security - Workflow Management **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image - Generative AI **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making - Third-Party Integrations ## Top Google Cloud AutoML Alternatives - [Azure Machine Learning](https://www.g2.com/products/microsoft-azure-machine-learning/reviews) - 4.3/5.0 (87 reviews) - [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews) - 4.3/5.0 (54 reviews) - [DataRobot](https://www.g2.com/products/datarobot/reviews) - 4.4/5.0 (40 reviews)