A surface defect, a lesion boundary, a damaged part: on images, the label is often a specialist's call. Kili puts that specialist in the image annotation workflow with Meta's SAM, boxes, polygons and segmentation, then measures quality with consensus, honeypot and review steps before data reaches your model.
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Your specialists spend their time on the calls only they can make. Quality engineers and clinicians label and review directly, while Consensus scores overlap on boxes, polygons and masks and honeypot assets test each labeler against a known answer. Because quality is measured as the work happens, no one waits for a recalibration round.
Your team labels the whole task in one place, so nothing is split across tools or stitched back together later. Boxes, polygons, lines, points, vectors, masks with Meta's SAM, pose points and image-level classification all live in one project, and labelers move fast on automatic or custom shortcuts.
Medical, industrial and defense imagery stays inside your boundary. Keep images in your own S3, Google Cloud Storage or Azure Blob bucket while Kili hosts the platform, or install Kili on your own Kubernetes with no internet access needed after installation. SOC 2 Type II and ISO 27001 certified, HIPAA compliant.
Speak to our team for a free 14-day evaluation.
Kili Technology is a complete data suite that supports all data types and handles specialized formats for domain-specific requirements.
Customer stories from the programs that put this to work — with the numbers behind them.
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Stay up to date with fresh content from our team — tutorials, use cases, and ideas to help you train AI/ML models better.
Got questions about Kili Technology? Check out our FAQ. If you can't find it in this list, drop a question for our team.
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