Keylabs vs Segments.ai
Keylabs
keylabs.aiSegments.ai
segments.aiSide by side
| Figure | Keylabs | Segments.ai |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | Yes | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 4 | 4 |
| Spec score · Image Annotation Software | 8.1 (#9) | 8.1 (#11) |
| Spec score · AI Image Annotation Tools | 8.1 (#8) | 8.1 (#9) |
| Company history | Keylabs says it began as a custom annotation tool built for its own needs and later developed into a flexible annotation platform. | Segments.ai says it launched in 2020 as a data labeling solution designed for segmentation. |
| Integrations | Keylabs lists integrations with AWS S3, Google Cloud, Azure, local storage, Roboflow, and Google Vision OCR. | The Python SDK supports programmatic data upload, label downloads, dataset management, and webhooks; the integrations page names TensorFlow and PyTorch. |
| Intended users | The infrastructure page names enterprise AI teams, data operations teams, ML engineers, and AI vendors as use cases. | The company describes the product as designed for computer vision engineers and data scientists working in autonomous robotics and driving. |
| Product | Keylabs is a data annotation platform for image, video, and 3D data, with AI assistance and built-in quality assurance. | Segments.ai is a multi-sensor data labeling platform for robotics and autonomous vehicle teams. |
| Support | The pricing page lists customer support hours per month as a plan feature but does not show the hour amounts in its text. | Fusion includes priority support and mail, Slack, and Discord support. |
Plans
Keylabs
- Startup$1, paid once
- Pro$2.10, paid once
- Business$2.30, paid once
- EnterprisePriced on request
Segments.ai
- Academic licenseFree
- CorePrice not published
- EnterprisePrice not published
- FusionPrice not published
In their own words
Segments.ai
Segments.ai is a data labeling platform for robotics and autonomous vehicle work, with tools for both images and 3D point clouds. Teams can mark data with segmentation, cuboids, bounding boxes, keypoints, polygons, and polylines, view images alongside point clouds, and project labels between sensors. For sequences, Batch Mode, merged point clouds, interpolation, and automated tracking support labeling across objects and frames. Image workflows include Superpixel, Autosegment, hover-and-click segmentation, and model predictions that teams can review and correct. Its Python SDK handles uploads, label downloads, dataset management, and webhooks; TensorFlow and PyTorch are named integrations. The product is available through web and API access, and datasets can be exported as JSON, PyTorch, TensorFlow, or Hugging Face formats. Core includes cloud bucket integrations. The company states it is EU based, ISO 27001 certified, and GDPR compliant. Pricing is on request, with a 14-day trial; a free academic license is available for non-commercial research at free.