About Segments.ai2024-02-19T16:16:28+01:00

Our history

In 2020, Segments.ai launched as a data labeling solution designed explicitly for segmentation. Initially, we had many customers in the robotics and autonomous driving industries. This stimulated us to address the complex needs of autonomous navigation, leading us to introduce point cloud support.

Through close collaboration with our customers, we quickly realized that manually labeling multiple modalities can be time-consuming, costly, and ineffective. Therefore, we shifted our focus towards providing multi-sensor support by integrating built-in projection steps and automation.

For robotics and autonomous driving

Automotive and robotics companies increasingly use lidar, radar, and camera sensors during labeling and deployment. The more sensors they use, the more accurate and robust their ML models become.

However, using additional sensors also requires more budget and time for development and training. According to a recent study, more than 70% of ML engineers spend over 50% of their time building training data.

Segments.ai is committed to providing the best solutions for computer vision engineers and data scientists who work in the autonomous sectors. Data labeling on Segments.ai seamlessly integrates with your pipelines and infrastructure, making it easier to build multi-sensor training data at scale and iteratively.


  • Founded in early 2020

  • Founded by Otto Debals (CEO) and Bert De Brabandere (CTO) after finishing their PhDs and gaining experience in the (automotive) industry
  • Funded in 2021 by YCombinator and other VC funds, including Merus Capital, Volta Ventures.
  • Segments.ai is ISO27001 certified, GDPR compliant and EU based

Trusted by computer vision engineers across robotics and AV companies

You leverage cutting-edge technologies

Latest News

The 8 Best Point Cloud Labeling Tools for 2024

February 23rd, 2024|

It's simply not enough to give a computer a large amount of data and expect it to learn – data has to undergo preparation for computers to find patterns within [...]

Better 3D sequence labeling, deep linking, and more

February 14th, 2024|

We’ve been hard at work in the first weeks of the new year to deliver you another round of exciting product updates. Let’s dive right in. Better 3D sequence labeling [...]

Building your internal data labeling software

January 29th, 2024|

Annotation or labeling tooling has multiple use cases. Think about labelling datasets to use for your ML pipeline or to highlight objects on an image to display on your [...]

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