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.

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.

5* - Great efficient tool with good UX and an extremely helpful Customer service team. Our main consideration for a tool was something that could handle an extremely large data set with around a million to 2 million images. We have shortlisted a lot of tools but we ended up choosing super-annotate as it had an user friendly UX and very high rate of annotation. The way we have handled a team of 40-50 annotators was very easy and hassle free.

I think they are the fastest to date. In terms of speed, SuperAnnotate beats out most of the competitors in the space. I love their automatic segmentation tool.

One of the best integrated annotation workflows I've used I am a scientific researcher in the biomedical imaging community, and I can say first-hand that the SuperAnnotate platform addresses a significant pain point for computer vision researchers. Obtaining expert annotations is often one of the first steps for a medical imaging project. Previously, I had used different open-source or commercial tools, but I often had to cobble together more than one piece of software to get a complete annotation pipeline. This was the first platform I've liked that includes an integrated, streamlined workflow for easy-to-use annotation (with AI augmentation), quality control, as well as neural network training. The team is responsive to feedback to improve the platform, and there are new features that I have yet to try but I am very pleased with the service as is. Note: I have also left a similar review on G2.