The best annotation tool in the market For our company, which specializes in ML solutions, we have tried several popular tools for image annotation/labeling, and SuperAnnotate had the easiest to use and the most relevant tool set for us. Particularly their automatic image segmentation is gold! It speeded up the process a lot. It's been more than a year we are using their services and we are very satisfied with it.

OAK-D deploy tool This annotation platform is so much trustworthy for development of computer vision on the edge tasks. Actually I'm working on deploying a detection model on the LUXONIS OAK-D, and has been a magnificent tool.

Best on the market For us as an ML first company, labeling quality has always been a top priority. So, while we were looking for potential annotation partners, SuperAnnotate stood out by being extremely supportive in setting up the pilot project in a speedy manner, so that we could assess labeling quality and velocity. Furthermore, they proactively onboarded us to their platform and are still very supportive as our projects are ongoing. Comparing to other companies we have worked with in the past, SA is the winner. Their platform offers an exceptional user experience that is well thought through, super easy to use, and also allows us to easily set up labeling and QA workflows such that our in-house QA team is seamlessly integrated into the process.

Great team, great product, great support We needed an experienced team with great software to help us develop a new pose detection algorithm. We needed to find the right model for our project which required experimentation and iteration with the annotation team. The Superannotate team has the right team at the right price. Their software, customer support and annotators did a great job of executing on our model.

SuperAnnotate: A great tool for data annotation SuperAnnotate is an awesome tool for the researchers/students who are working with the dataset preparation for computer vision related applications such as environment perception including object detection and semantic segmentation. It helped me a lot in my Masters' thesis. Recommended.