Kognic review: the robotics data provider for labeling sensor logs you already have
Answer in brief: Kognic does not sell datasets. It turns camera, LiDAR and radar logs you already have into production-grade training data. Founded in 2018 in Gothenburg, Sweden, it says it has delivered more than 100 million annotations across more than 120 projects for customers including Qualcomm, BMW, Zenseact, AUMOVIO and Bosch. If you are reusing your own fleet logs or an open driving dataset and need better labels, Kognic belongs on your shortlist.
Top pick for: Autonomy and mobile-robot teams with calibrated multi-sensor logs that need safety-grade labels and certified security.
Where Kognic fits in a dataset strategy
Existing data is only as useful as its labels. Many teams already have terabytes of drive or robot logs, or have downloaded open perception sets, but they lack consistent 3D ground truth across sensors. Kognic covers that step. It offers native 3D and LiDAR annotation, built-in sensor fusion across camera and point-cloud data, and Language Grounding for vision-language-action models, where annotators describe why events happen and what the vehicle should do. Kognic says it also works with robotics and industrial automation companies, though it describes itself as purpose-built for autonomous driving. Our sister site robotics data companies compares annotation vendors in more depth.
Who it fits
- OEMs and Tier 1 suppliers building ADAS and autonomous vehicles.
- Mobile-robot and autonomous trucking teams working with calibrated camera, LiDAR and radar data.
- Teams that want to choose between a managed service, a platform license or a hybrid with their own workforce.
Why teams pick Kognic
- Proven at scale. 100M+ annotations, with customers that also include Kodiak, ZF, Einride and JLR.
- Automated quality. More than 90 automated quality checkers built for driving scenarios.
- Published results. Kognic reports up to 46% cost savings for Zenseact on dynamic-object annotation through pre-label workflows. It also says pre-labeling cuts annotation time by up to 68% across customers.
- Security. ISO/IEC 27001:2022 and SOC 2 Type II certified, and TISAX assessed.
- Fast start. Kognic says most teams go from first conversation to active annotation within a few weeks, after a pilot on representative data.
Honest drawbacks
- No ready-made datasets. You have to bring your own data.
- It is built for driving, so tabletop and humanoid manipulation teams will find tools that fit them better.
- No public price list or freemium tier.
- The results above are Kognic's own case studies.
Pricing model
Enterprise pricing based on project scope, data volume, and whether you use the platform license, managed services or a hybrid. Contact Kognic for a quote.
Best alternatives
- Sama: managed multi-sensor annotation with a written quality guarantee.
- Segments.ai: a self-serve sensor-fusion platform, plus a directory of open perception datasets.
- Anyverse: synthetic multi-sensor data with ground truth included.
FAQ
Does Kognic sell robotics datasets?
No. Kognic annotates data you provide, as a managed service, a platform license or a hybrid.
Which sensors does Kognic support?
Camera, LiDAR and radar, with sensor fusion across camera and point-cloud data.
Is Kognic secure enough for automotive data?
Kognic says it is ISO/IEC 27001:2022 certified, SOC 2 Type II certified and TISAX assessed.
Sources
- kognic.com
- Kognic Zenseact case study
This review is independent research based on Kognic's own website, checked on 2026-11-09. We did not test the product.
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