Segments.ai
Segments.ai is a multi-sensor data labeling platform for robotics and autonomous vehicle teams, available through web and API access.
What Segments.ai is
Segments.ai is a multi-sensor data labeling platform for robotics and autonomous vehicle teams, available through web and API access. It supports image and point-cloud annotation with segmentation, cuboids, bounding boxes, keypoints, polygons, and polylines. Teams can view 2D images with 3D point clouds and project labels between sensors. For 3D sequences, Batch Mode, merged point clouds, interpolation, and automated tracking support annotation across objects and frames. Image tools include Superpixel, Autosegment, hover-and-click segmentation, and uploaded model predictions for review and correction. Its Python SDK supports programmatic uploads, label downloads, dataset management, and webhooks; TensorFlow and PyTorch are named integrations. The company says the platform is designed for computer vision engineers and data scientists working in autonomous robotics and driving, and that it launched in 2020 as a segmentation-focused labeling solution. A free academic license is available for non-commercial research, subject to a license request. Core, Fusion, and Enterprise pricing is by custom quote; Core limits point clouds to 500,000 points each, while Fusion includes point clouds and images of unlimited size and resolution.
Good
- Labels images and point clouds
- Projects labels between sensors
- Includes sequence annotation tools
- Python SDK supports uploads, downloads, and webhooks
- Names TensorFlow and PyTorch integrations
Watch out
- Core point clouds are limited to 500,000 points each
- Academic license requires a request
- Core, Fusion, and Enterprise prices are custom quotes
Who it suits
Segments.ai suits computer vision engineers and data scientists labeling data for autonomous robotics or driving. Its free academic license is for non-commercial research and requires a license request.
Verdict
Segments.ai combines multi-sensor labeling with sequence tools and model-assisted image annotation. Teams should check the Core point limit and request pricing for the other listed plans.
Plans and prices
From Segments.ai's own pricing page, checked 8 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Academic license | Free | For students and researchers with non-commercial academic use · License request required · 100% free for non-commercial academic research |
| Core | — | Unlimited seats · Unlimited projects · Unlimited images and point clouds · Unlimited API and SDK access · Point clouds up to 500,000 points each · ML labeling tools · Cloud bucket integrations · QA and organization management · Custom quote; starting at 3,600 hours/year (equivalent to $2.67/hour) |
| Enterprise | — | Unlimited seats · Unlimited projects · Unlimited images and point clouds · Unlimited API and SDK access · Custom interfaces · Custom pipelines and workflows · Technical-roadmap influence · Custom security solutions · Custom quote; includes 150,000+ hours/year |
| Fusion | — | Unlimited seats · Unlimited projects · Unlimited images and point clouds · Unlimited API and SDK access · Unlimited-size point clouds and images · Sensor fusion interfaces · Webhooks · Priority support · Metrics dashboard · Labeling workforce access · Mail, Slack and Discord support · Custom quote; starting at 5,000 hours/year |
The facts
Each one read from Segments.ai's own pages, with the date it was checked.
What it does
- 2D and 3D annotation
- The platform supports image and point-cloud labeling with segmentation, cuboids, bounding boxes, keypoints, polygons, and polylines.checked 8 Oct 2026
- 2D annotation tools
- Image labeling supports semantic, instance and panoptic segmentation plus bounding boxes, polygons, polylines, keypoints, superpixels, Autosegment and hover-and-click tools.checked 15 Oct 2026
- 3D point-cloud tools
- 3D workflows include cuboids, segmentation, keypoints, polygons, polylines, merged point-cloud mode, batch mode and automated tracking.checked 15 Oct 2026
- 3D sequence tools
- Batch Mode, merged point clouds, interpolation, and automated tracking support labeling objects across sequences.checked 8 Oct 2026
- API scope
- The documented API covers datasets, samples, labels, labelsets and releases for programmatic annotation workflows.checked 15 Oct 2026
- Asset upload limit
- The platform's own asset-storage service limits uploaded files to 100 MB and stores them in an AWS S3 bucket in London.checked 15 Oct 2026
- Cloud integrations
- Documentation describes AWS S3 cross-account access, Azure Blob Link Service and keeping assets in customer-managed cloud buckets.checked 15 Oct 2026
- Cloud storage
- The Core plan includes cloud bucket integrations.checked 8 Oct 2026
- Customer-controlled storage
- For production, documentation recommends retaining data in the customer's own bucket and sending URLs, including presigned or cross-account URLs.checked 15 Oct 2026
- Documentation coverage
- The documentation includes getting-started tutorials, API reference, API-key setup, import guidance, cloud integrations and Python SDK instructions.checked 15 Oct 2026
- Enterprise access
- Enterprise includes SSO and MFA, custom security solutions, and a dedicated solutions ML engineer.checked 8 Oct 2026
- Founders
- Y Combinator identifies Otto Debals and Bert De Brabandere as founders; Crunchbase also lists Davy Neven among the founders.checked 15 Oct 2026
- Funding
- Y Combinator says the company was funded in 2021 by Y Combinator, Merus Capital and Volta Ventures.checked 15 Oct 2026
- Integrations
- The Python SDK supports programmatic data upload, label downloads, dataset management, and webhooks; the integrations page names TensorFlow and PyTorch.checked 8 Oct 2026
- Intended users
- The company describes the product as designed for computer vision engineers and data scientists working in autonomous robotics and driving.checked 8 Oct 2026
- Legal entity
- Crunchbase identifies the legal name as Segments.ai BV and lists Leuven, Belgium as headquarters.checked 15 Oct 2026
- Limit: heavy 3D workloads
- Individual G2 reviews report slow or stuck 3D visualization on computationally heavy or large point-cloud sequences.checked 15 Oct 2026
- Limit: learning curve
- G2 review summaries repeatedly mention a steep learning curve for newcomers, complex features and insufficient guidance.checked 15 Oct 2026
- Limit: training and exports
- G2 reviewers report limited tutorials, a lack of training material and a desire for better direct web export options.checked 15 Oct 2026
- ML-assisted labeling
- Image tools include Superpixel, Autosegment, hover-and-click segmentation, and uploaded model predictions for review and correction.checked 8 Oct 2026
The company
- Company history
- Segments.ai says it launched in 2020 as a data labeling solution designed for segmentation.checked 8 Oct 2026
- Company size and base
- LinkedIn lists Segments.ai by Uber as a Leuven, Belgium software-development company with 11–50 employees and a 2020 founding year.checked 15 Oct 2026
- Founded
- 2020checked 28 Sep 2026
Where it runs
- GetApp listing
- GetApp's October 2026 listing shows no user reviews and a 0.0 score for ease of use, features, value and support.checked 15 Oct 2026
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