Case studies

Databricks collaborates with SuperAnnotate to refine RAG systems, ensuring consistent LLM evaluations and streamlined feedback.

Learn how SuperAnnotate helped Twelve Labs build quality training datasets & cut multimodal AI development time by 50%.

Learn how GumGum, a leader in Contextual Intelligence, fine-tunes LMs with SuperAnnotate and Databricks.

Discover how SuperAnnotate optimized REM People’s workflow, enabling them to maintain their competitive edge in a fast-paced market.

Learn how SuperAnnotate helped Prairie Robotics reduce recycling contamination by 40% and drive a sustainable future.

Find out how Hinge Health achieved massive improvements in annotation accuracy, accelerated annotation/QA speed, and reduced costs with SuperAnnotate.

Learn how Orsi leveraged the power of SuperAnnotate to achieve 3x faster labeling and superior annotation quality compared to physician annotators.

Discover how SuperAnnotate helped OneCup cut data annotation costs, expedite quality assurance, and boost model performance, all within one platform.

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.