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bage-icon The leader in autonomy data annotation

Machines learn faster with Human Feedback

Integrate cost-efficient, scalable human feedback into your autonomy data flywheel.

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Qualcomm
Continental
Bosch
Kodiak
ZF
Embotech
Einride
Gatik
JLR
Sama

Pushing the frontier of autonomous data annotation

Autonomy is evolving fast, moving from perception toward richer forms of understanding and decision-making. At Kognic, we push the frontier of annotation. We are extending human feedback beyond routine tasks into emerging needs like trajectory ranking, multimodal grounding, and Visual-Language-Action models.

 

We ensure annotation keeps pace with the next generation of autonomous systems.

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How do we scale our annotation pipeline for higher volumes?
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How can we maintain quality while increasing throughput?
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What's the best way to integrate auto-labeling?
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How can we reduce costs while preserving quality?
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How do we handle multi-modal data?
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What's the best way to manage annotation teams?
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How do we ensure consistency between annotators?
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Which metrics matter for optimization?
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How do we handle edge cases?
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Can we integrate with existing pipelines?
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How do we maintain security at scale?
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What's the best way to annotate LiDAR and radar data?
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How can we speed up data processing?
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How should we version datasets?
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How do we meet regulatory requirements?
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How do we validate annotation quality?

The data you need to win

Maximum volume without sacrificing safety, trust, or compliance. The more great data you feed your models, the better your product will perform.

End-to-End Pipeline Integration

From raw sensor data to validated datasets, we handle your complete annotation workflow.
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For ML Engineers

  • Process complex multi-modal data with proven tools built for autonomy
  • Leverage intelligent auto-labeling integration to accelerate development
Technical Details
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For Technical Leaders

  • Scale annotation operations without compromising on quality or security
  • Track metrics and costs with comprehensive project analytics
Platform Architecture
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For Annotation Teams

  • Work efficiently with purpose-built tools for autonomous systems data
  • Maintain consistency through structured workflows and continuous training
Annotation Tools

Your data, your way.

Choose the deployment model that best fits your development pipeline and team structure.

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Managed Service
Access our complete platform and expert annotation partners.
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Platform License
Deploy our annotation tools within your existing workflows.
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Hybrid Solution
Combine our platform with your preferred workforce solution.

“Kognic provides the possibility to go all in and rely 100% on their services if needed, or to come up with a mix where we would use their services and our internals combined.

This is a really powerful offering that we haven't seen a lot of the competitors willing to do.”

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Gergely Barot Kovacs

Product Manager, Continental

Continental Accelerated 3D Ground Truth Development

When Continental needed to enhance their perception development work, they partnered with Kognic to streamline their 3D ground truth generation. Through Kognic's platform, they achieved more efficient labeling processes and flexible workforce management.

Integrated powerful data pipelines tailored to complex urban driving scenarios
Read Case Study

Our recent articles

Stay up to date with the latest insights on labelling.

A Backender’s Journey; Going From an Entangled Monolithic Codebase to a Loosely Coupled Domain Driven Codebase
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A Backender’s Journey; Going From an Entangled Monolithic Codebase to a Loosely Coupled Domain Driven Codebase

Learn how a backender's journey led to transforming an entangled monolithic codebase into a loosely coupled domain-driven codebase, improving collaboration and engineering velocity.
Kognic Product Updates – September 2025
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Kognic Product Updates – September 2025

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🌍 Understanding 3D Semantic Segmentation
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8 September 2025

🌍 Understanding 3D Semantic Segmentation

Discover the importance of 3D semantic segmentation for autonomous systems and how Kognic's innovative tools enhance annotation efficiency and accuracy.
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