Case studies

IntelinAir shares how they were able to build pixel-accurate training data at quality levels and speeds unachievable with their previous tooling.

SuperAnnotate’s advanced automation features helped AEDIT automate its data training processes. AEDIT was also able to increase model accuracy by 6%.

Learn how Percepto was able to implement a scalable annotation infrastructure, find high-quality outsourced annotation teams and get lightning-fast annotations.

SuperAnnotate’s pixel-accurate and user-friendly tools, particularly the Smart Segmentation tool, improved the quality of Spacept’s annotations.

Altris AI compared SuperAnnotate and Labelbox and shared how SuperAnnotate decreased their annotation cost and drastically increased their annotation quality.

Learn how researchers at the TACK project are using SuperAnnotate to speed up image annotation of their project.