Segments.ai
segments.ai
What it is
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.
Spec sheet
- What it does
- Segments.ai is a cloud data-labeling platform for computer-vision, robotics and autonomous-vehicle teams, supporting images, videos, point clouds and multi-sensor data.Read 15 Oct 2026 · segments.ai
- Product
- Segments.ai is a multi-sensor data labeling platform for robotics and autonomous vehicle teams.Read 8 Oct 2026 · segments.ai
- Intended users
- The company describes the product as designed for computer vision engineers and data scientists working in autonomous robotics and driving.Read 8 Oct 2026 · segments.ai
- Integrations
- The Python SDK supports programmatic data upload, label downloads, dataset management, and webhooks; the integrations page names TensorFlow and PyTorch.Read 8 Oct 2026 · segments.ai
- Support
- Fusion includes priority support and mail, Slack, and Discord support.Read 8 Oct 2026 · segments.ai
- Founded
- 2020Read 28 Sep 2026 · segments.ai
- 2D and 3D annotation
- The platform supports image and point-cloud labeling with segmentation, cuboids, bounding boxes, keypoints, polygons, and polylines.Read 8 Oct 2026 · segments.ai
- 2D annotation tools
- Image labeling supports semantic, instance and panoptic segmentation plus bounding boxes, polygons, polylines, keypoints, superpixels, Autosegment and hover-and-click tools.Read 15 Oct 2026 · segments.ai
- 3D point-cloud tools
- 3D workflows include cuboids, segmentation, keypoints, polygons, polylines, merged point-cloud mode, batch mode and automated tracking.Read 15 Oct 2026 · segments.ai
- 3D sequence tools
- Batch Mode, merged point clouds, interpolation, and automated tracking support labeling objects across sequences.Read 8 Oct 2026 · segments.ai
- API scope
- The documented API covers datasets, samples, labels, labelsets and releases for programmatic annotation workflows.Read 15 Oct 2026 · docs.segments.ai
- 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.Read 15 Oct 2026 · docs.segments.ai
- Cloud integrations
- Documentation describes AWS S3 cross-account access, Azure Blob Link Service and keeping assets in customer-managed cloud buckets.Read 15 Oct 2026 · docs.segments.ai
- Cloud storage
- The Core plan includes cloud bucket integrations.Read 8 Oct 2026 · segments.ai
- Company history
- Segments.ai says it launched in 2020 as a data labeling solution designed for segmentation.Read 8 Oct 2026 · segments.ai
- 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.Read 15 Oct 2026 · linkedin.com
- Customer-controlled storage
- For production, documentation recommends retaining data in the customer's own bucket and sending URLs, including presigned or cross-account URLs.Read 15 Oct 2026 · docs.segments.ai
- Documentation coverage
- The documentation includes getting-started tutorials, API reference, API-key setup, import guidance, cloud integrations and Python SDK instructions.Read 15 Oct 2026 · docs.segments.ai
- Enterprise access
- Enterprise includes SSO and MFA, custom security solutions, and a dedicated solutions ML engineer.Read 8 Oct 2026 · segments.ai
- Founders
- Y Combinator identifies Otto Debals and Bert De Brabandere as founders; Crunchbase also lists Davy Neven among the founders.Read 15 Oct 2026 · ycombinator.com
- Funding
- Y Combinator says the company was funded in 2021 by Y Combinator, Merus Capital and Volta Ventures.Read 15 Oct 2026 · ycombinator.com
- GetApp listing
- GetApp's October 2026 listing shows no user reviews and a 0.0 score for ease of use, features, value and support.Read 15 Oct 2026 · getapp.com
- Legal entity
- Crunchbase identifies the legal name as Segments.ai BV and lists Leuven, Belgium as headquarters.Read 15 Oct 2026 · crunchbase.com
- Limit: heavy 3D workloads
- Individual G2 reviews report slow or stuck 3D visualization on computationally heavy or large point-cloud sequences.Read 15 Oct 2026 · g2.com
- Limit: learning curve
- G2 review summaries repeatedly mention a steep learning curve for newcomers, complex features and insufficient guidance.Read 15 Oct 2026 · g2.com
- Limit: training and exports
- G2 reviewers report limited tutorials, a lack of training material and a desire for better direct web export options.Read 15 Oct 2026 · g2.com
- ML-assisted labeling
- Image tools include Superpixel, Autosegment, hover-and-click segmentation, and uploaded model predictions for review and correction.Read 8 Oct 2026 · segments.ai
- ML-framework integrations
- The company states that exports and integrations cover PyTorch, TensorFlow, Hugging Face and other machine-learning stack vendors.Read 15 Oct 2026 · segments.ai
- Model-assisted labeling
- Users can upload model predictions as pre-labels, verify them and correct errors inside the platform.Read 15 Oct 2026 · segments.ai
- Multi-sensor labeling
- The interface displays and labels multiple sensor modalities together and can project labels between 3D and 2D data.Read 15 Oct 2026 · segments.ai
- Multi-sensor workflow
- Users can view 2D images and 3D point clouds together and project labels between sensors.Read 8 Oct 2026 · segments.ai
- Notable limit
- Core supports point clouds of up to 500,000 points each; Fusion includes point clouds and images of unlimited size and resolution.Read 8 Oct 2026 · segments.ai
- Ownership
- Crunchbase lists Segments.ai as acquired by Uber.Read 15 Oct 2026 · crunchbase.com
- Praise: support and SDK
- G2 reviewers repeatedly describe support as fast and helpful and praise the Python SDK for downloading images and segmentation outputs.Read 15 Oct 2026 · g2.com
- Praise: usability and speed
- G2 reviewers repeatedly praise the intuitive interface, fast image labeling, accurate segmentation and quick processing of large images.Read 15 Oct 2026 · g2.com
- Public API
- A REST API is available at https://api.segments.ai/ and uses API-key authentication in an Authorization header.Read 15 Oct 2026 · docs.segments.ai
- Python SDK
- The Python SDK is installed with pip, exposes SegmentsClient, and supports dataset creation, sample upload, labeling and release export.Read 15 Oct 2026 · docs.segments.ai
- Rating on G2
- 4.6 out of 5 from 22 reviews.Read 15 Oct 2026 · g2.com
- Recent product news
- The home page lists a May 28, 2026 article titled “The 8 Best Point Cloud Labeling Tools for 2026.”Read 15 Oct 2026 · segments.ai
- SDK license
- The public Segments.ai Python SDK repository is marked MIT licensed.Read 15 Oct 2026 · github.com
- Security and compliance
- Company materials state that Segments.ai is ISO 27001 certified, GDPR compliant and EU based.Read 15 Oct 2026 · ycombinator.com
- Self-hosting
- The product is presented as a cloud platform; the reviewed documentation provides cloud access and customer-bucket options but no self-hosted deployment package.Read 15 Oct 2026 · segments.ai
- Status monitoring
- An unofficial SaaSHub monitor reported Segments.ai up, with no reported issues in the prior 24 hours and 100% monitored uptime over the prior 30 days.Read 15 Oct 2026 · saashub.com
- Video labeling
- Video and sequence workflows provide interpolation, ML assistance and merged 3D point-cloud views.Read 15 Oct 2026 · g2.com
Plans and prices
Strong points and limits
Strong points
- Labels images and point clouds across six annotation types
- Projects labels between sensors
- Python SDK supports uploads, downloads, and webhooks
- Exports to JSON, PyTorch, TensorFlow, and Hugging Face
Limits
- Core point clouds are limited to 500,000 points each
- Academic license requires a request
- Core, Fusion, and Enterprise pricing is by custom quote
Who it suits
It suits computer vision engineers and data scientists labeling image and point-cloud data for autonomous robotics and driving. The academic license is for students and researchers doing non-commercial academic work, with a license request required.
Verdict
Segments.ai covers multi-sensor labeling, sequence workflows, and model-assisted image annotation. Check the Core point limit and request pricing to determine whether its plans fit the dataset and workload.
Where Specifiction places it
- AI Image Annotation Tools#9 of 248.1
- Image Annotation Software#11 of 288.1
- Data Labeling Software#13 of 248.0