Advertima accelerates video data labeling 10-15x with super.AI
Advertima's cashierless checkout solution required large-scale video labeling, but their open-source tool CVAT was slow, buggy, and had long turnaround times, generating significant overhead when ingesting proprietary camera data.
CVAT, the open-source video labeling tool Advertima was using, proved too slow and buggy with limited UX and long processing turnarounds, making it unfit for their proprietary camera footage volume.
super.AI processed hundreds of hours of video footage 10-15 times faster than CVAT with greater accuracy.
Frequently asked questions
What did this team achieve with this AI workflow?
super.AI processed hundreds of hours of video footage 10-15 times faster than CVAT with greater accuracy.
What tools did this team use?
super.AI, CVAT.
What results were reported?
Video processing time: 10-15 times; Labeling accuracy: greater accuracy (source-reported, not independently verified).
What failed first in this deployment?
CVAT, the open-source video labeling tool Advertima was using, proved too slow and buggy with limited UX and long processing turnarounds, making it unfit for their proprietary camera footage volume.
How is this data entry ops AI workflow structured?
Video footage submitted via API → AI labels video content → Processed labeled data returned.