SuperAnnotate Pro
SuperAnnotateReviews from AWS customer
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Efficient Annotation with Room for Speed Improvement
What do you like best about the product?
I use SuperAnnotate for annotation tasks on images and datasets. I appreciate how it keeps my work organized and makes managing tasks easier. The tools are easy to use, and the platform is simple to work with, which helps me finish tasks faster without spending time figuring out how things work. The initial setup was easy, and I could start working quickly.
What do you dislike about the product?
Sometimes it can feel a bit slow with larger tasks. Better performance with larger tasks would make the experience smoother.
What problems is the product solving and how is that benefiting you?
I use SuperAnnotate because it keeps annotation work organized and easy to manage. Its simple tools help me finish tasks faster without spending time figuring out how things work.
Streamlined Annotation, Boosted Productivity
What do you like best about the product?
I love SuperAnnotate's user-friendly interface and powerful annotation tools that make labeling tasks faster and more accurate. The platform’s collaboration features, version control, and built-in quality checks help maintain consistency across large projects, reduce rework, and make teamwork smooth and efficient, improving overall productivity and confidence in the final datasets. Setting it up was easy, with an intuitive interface and a well-guided onboarding process that allowed us to start working productively without major technical difficulties.
What do you dislike about the product?
There are a few things about SuperAnnotate that could be improved, such as occasional performance slowdowns when working with very large datasets and the learning curve for new users who may find some advanced features complex at first. Additionally, expanding customization options and improving shortcut support could make the workflow even smoother and more efficient, especially for teams handling high-volume or highly detailed annotation tasks.
What problems is the product solving and how is that benefiting you?
I use SuperAnnotate to efficiently annotate datasets for AI projects, reducing manual errors, saving time, and streamlining team collaboration. It ensures consistent and high-quality annotations, crucial for training accurate models.
Revolutionized Our Data Labeling Efficiency
What do you like best about the product?
I find SuperAnnotate to be a lifesaver for our pipeline. The auto-labeling tools actually work, and the modern UI is fast and helps cut our manual work in half. I appreciate the AI-powered Auto-annotate tools and the robust multilevel QA workflows that solve the problem of 'dirty' data while significantly reducing our production time. I like that it’s a modern, all-in-one ecosystem that handles everything from complex video segmentation to RLHF in a single, intuitive interface. It really eliminates the manual grind of traditional data entry and centralizes the whole team in one spot, allowing us to focus on training models with high-quality data. The initial setup was incredibly smooth, and the platform's modern, Photoshop-like UI along with pre-built templates made onboarding intuitive. I also enjoy how it integrates with cloud storage like AWS S3 and Google Cloud, and connects with Amazon SageMaker and Databricks, which allows us to efficiently push labeled data into training environments. Lastly, I love how it consolidated everything into a fast, automated environment, saving our team hours of coordination.
What do you dislike about the product?
While SuperAnnotate is powerful, the enterprise-grade pricing makes it a tough pill to swallow for smaller startups, especially since the best automation features are locked behind higher tiers. The platform also has a steeper learning curve for its more advanced functions; setting up complex workflows often requires a technical background rather than being a 'plug-and-play' experience. Additionally, the lack of nested subfolder support forces us to flatten our data structures before uploading, and the reporting dashboards can occasionally lag, requiring manual refreshes to see real-time progress. Improving the 'no-code' accessibility for advanced filters and smoothing out the file hierarchy would go a long way in making the tool more user-friendly for non-technical managers.
What problems is the product solving and how is that benefiting you?
SuperAnnotate eliminates the manual grind by automating labeling and centralizing our team, reducing busy work and letting us focus on training models. It cuts production time by 50% and handles everything in a modern, intuitive interface.
Accelerates Annotation with AI Assistance
What do you like best about the product?
I use SuperAnnotate to label and manage datasets for machine learning projects, and it really helps with image and text annotation, quality control, and team collaboration. What I like most is the AI-assisted annotation and built-in quality control. These features speed up labeling, reduce errors, and make collaboration smooth, even on large datasets. AI-assisted annotation reduces manual work by pre-labeling data, while built-in quality control ensures consistency through reviews and checks. Together, they cut rework, save time, and make the final datasets more reliable for training models.
What do you dislike about the product?
I find the learning curve challenging; the interface and advanced features take time to learn. Working with very large images or long videos can be slow. Also, the cost feels high for small teams if you're not working at scale.
What problems is the product solving and how is that benefiting you?
I use SuperAnnotate to label and manage datasets for machine learning projects. It saves time and improves data quality by solving slow manual labeling, inconsistent annotations, and poor quality control with AI-assisted labeling, review workflows, and easy team collaboration.
Intuitive Collaboration Platform for AI Projects
What do you like best about the product?
I use SuperAnnotate for annotating and reviewing data for AI and machine learning projects, and I really like how intuitive and structured the platform is. The smooth collaboration and review workflow stand out to me, along with its ability to keep large annotation projects organized and easy to track. It helps me maintain consistency and quality across datasets, saving time and reducing errors in AI training workflows. Additionally, SuperAnnotate offers better collaboration features and more efficient project management compared to the basic annotation tool we previously used. Setting it up was fairly straightforward, with the basic setup being easy.
What do you dislike about the product?
Some advanced features could be more intuitive, performance can slow down with very large projects, and clearer in-platform guidance or tutorials would make onboarding easier.
What problems is the product solving and how is that benefiting you?
I use SuperAnnotate to organize large annotation tasks, maintain consistency and quality, and collaborate efficiently with teams, which saves time and reduces errors in AI training workflows.
Intuitive Interface with Strong Collaboration Features
What do you like best about the product?
I use SuperAnnotate for annotating and reviewing datasets for machine learning projects, mainly for image and text labeling, quality checks, and collaborating with distributed teams. I like how intuitive the interface is, which lets me get started quickly without a steep learning curve. The smooth collaboration features make it easy to work with others in real time, track progress, and maintain consistent annotation quality. SuperAnnotate helps me organize annotation workflows, maintain consistent quality across tasks, and collaborate efficiently, saving me time and reducing errors in large-scale annotation projects. The initial setup was fairly easy and straightforward, with clear onboarding steps and documentation that helped me get up and running quickly. It's reliable, user-friendly, and well-suited for collaborative annotation work.
What do you dislike about the product?
Some advanced features take time to fully understand, and occasional performance slowdowns on very large projects could be improved. Additionally, some of the automation and customization options aren't immediately obvious and could benefit from clearer in-app guidance or examples. Better optimization for heavy datasets and more responsive loading would make the experience smoother.
What problems is the product solving and how is that benefiting you?
SuperAnnotate helps me organize annotation workflows, maintain consistent quality, and collaborate efficiently, saving time and reducing errors in large-scale annotation projects.
Improving AI tools
What do you like best about the product?
Ease of use, fast and reliable, very easy to setup
What do you dislike about the product?
I don't dislike anything, I really enjoy using the tool
What problems is the product solving and how is that benefiting you?
SuperAnnotate solves the core bottleneck in AI development — getting large volumes of high-quality labeled data — by combining powerful annotation tools, automation, workflow management, and quality assurance in a single platform.
The benefit to you is faster, more reliable dataset creation, better team coordination, and higher-performing ML models with less manual work.
The benefit to you is faster, more reliable dataset creation, better team coordination, and higher-performing ML models with less manual work.
Extraordinary SuperAnnotate Experience: Easy Navigation, Accurate Time Tracking, On-Time Pay
What do you like best about the product?
I have been using the SuperAnnotate platform for about one year as a Annotator and QA, and have worked on nearly 10 projects. I have also used other data annotation platforms, but my experience with SuperAnnotate has been the best.
The platform is very easy to use and navigate. Everything is well organized, and most tasks can be done with very few clicks. The overall user experience is smooth and beginner-friendly.
Time tracking on the platform is accurate and reliable. I have never faced any issues with time logging. Annotators can easily check their daily and weekly time summaries, which helps in tracking work properly.
Payments are made on time every week, which I really appreciate. This gives confidence and trust in the platform.
For communication, SuperAnnotate uses Discord channels. The support team and project managers are very responsive, and queries are usually answered quickly. Overall, the platform is professional, reliable, and pleasant to work with.
The platform is very easy to use and navigate. Everything is well organized, and most tasks can be done with very few clicks. The overall user experience is smooth and beginner-friendly.
Time tracking on the platform is accurate and reliable. I have never faced any issues with time logging. Annotators can easily check their daily and weekly time summaries, which helps in tracking work properly.
Payments are made on time every week, which I really appreciate. This gives confidence and trust in the platform.
For communication, SuperAnnotate uses Discord channels. The support team and project managers are very responsive, and queries are usually answered quickly. Overall, the platform is professional, reliable, and pleasant to work with.
What do you dislike about the product?
I would like to suggest enabling an Analytics Dashboard for each project. This dashboard would allow annotators to track the status of their items and monitor working time in real time. It would improve transparency and make work tracking easier and more efficient for annotators.
What problems is the product solving and how is that benefiting you?
SuperAnnotate solves data annotation and dataset management challenges by providing a unified platform to create, manage, and label high-quality training data for AI models. It supports multimodal annotation, custom workflows, and strong quality control, reducing manual effort and speeding up project delivery. This helps me work efficiently, meet deadlines, and deliver accurate and reliable results from one platform.
Boosted Linguistic Data Annotation Efficiency
What do you like best about the product?
I use SuperAnnotate for its intuitive interface and flexibility, which make annotating linguistic data efficient and accurate. I like the collaboration features that allow me to work seamlessly with my team. The project management and review features are also great, helping maintain consistency and high quality across large linguistic datasets. Setting up SuperAnnotate was straightforward and user friendly, letting me start annotating linguistic data quickly. It's much more efficient and user-friendly than the annotation tools we used before.
What do you dislike about the product?
I don’t have major issues with SuperAnnotate.
What problems is the product solving and how is that benefiting you?
I use SuperAnnotate to organize and accurately annotate linguistic data, ensuring high-quality datasets for AI language projects. It's efficient with an intuitive interface and enhances collaboration with my team.
Sleek, User-Friendly Platform That Makes Data Annotation Simple
What do you like best about the product?
SuperAnnotate has a sleek and user-friendly product that makes complex data annotation feel simple. The platform is modern, intuitive, and clearly designed with the user in mind.
What do you dislike about the product?
One thing that could be improved in SuperAnnotate is that, as the platform grows, some advanced features might feel a bit complex for new users. While the product is powerful, there can be a learning curve when getting started.
What problems is the product solving and how is that benefiting you?
helps solve the challenge of creating high-quality, accurate data annotations quickly. It makes the labeling process much more efficient, saving time for teams and allowing AI models to be trained faster and more reliably.
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