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Data Annotation for Mobility and Autonomous Systems

Train perception, prediction, and planning models on precisely labeled camera, LiDAR, and radar data. Smart Annotahub delivers consistent labels across sensors, frames, and edge cases.

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AI Use Cases We Support in Mobility and Autonomous Systems

01

Object Detection

Vehicles, pedestrians, cyclists, and road users across weather, lighting, and occlusion.

02

Lane and Road Understanding

Lane lines, drivable area, curbs, and road markings for path planning.

03

Traffic Signs and Lights

Sign classification and signal state for regulatory compliance.

04

3D Perception

LiDAR cuboids and point-level segmentation with consistent tracking IDs.

05

Sensor Fusion

Linked 2D and 3D labels across camera and LiDAR using your calibration.

06

Driver Monitoring

In-cabin gaze, pose, and distraction labels for safety systems.

Annotation Services for Mobility and Autonomous Systems

The data types mobility and autonomous systems teams send us most often. Every service starts with a free pilot.

Image Annotation Boxes, polygons, keypoints and segmentation. Video Annotation Tracking, actions and events across frames. 3D Point Cloud Annotation LiDAR cuboids and point-level segmentation.

How We Deliver Your Project

From your first sample to production volume, every project follows the same six-step path, with no commitment until the pilot proves the quality.

  1. Step 01

    NDA and Discovery

    We sign an NDA first, then clarify your goals, taxonomy, edge cases, and target accuracy for your dataset.

  2. Step 02

    Free Pilot

    We annotate a sample of your data at no cost, so you can judge quality, speed, and edge-case handling first-hand.

  3. Step 03

    Proposal and Agreement

    Based on your pilot feedback, we finalize scope, timeline, pricing, and the Service Level Agreement.

  4. Step 04

    Team Setup and Training

    We assemble a dedicated team, train it on your guidelines, and agree on communication channels and progress tracking.

  5. Step 05

    Production Labeling

    Our team runs annotation to the agreed plan, with throughput and accuracy KPIs tracked for every annotator.

  6. Step 06

    QA and Delivery

    Your labeled data pass multi-stage quality review before delivery. Your feedback feeds straight back into the guidelines.

Why AI Teams Choose Smart Annotahub

Handle Complex Datasets

Get consistent annotation for detailed taxonomies, edge cases, and challenging data.

Build Quality Into Every Step

We combine onboarding, clear and evolving guidelines, quality assurance, and continuous feedback.

Flexible and Scale On Your Terms

Adjust team capacity, project size, and delivery model as your needs change, with no setup fees or long-term lock-ins.

Integrate From Day One

Align on goals, workflows, and expectations with a team that fits into your process.

Work with Annotation Experts

Our team includes former annotators who understand annotation complexity, quality standards, and high-volume delivery.

Reviews

From our Clients

★★★★★

“Their flexibility and ability to move fast impress us.”

We chose Smart Annotahub for its strong value, recommendation, and shared company values. Their 10-person team delivered accurate data annotation with a flexible, collaborative approach. They responded quickly, went the extra mile to meet deadlines, and kept the project on track. We’ve been very pleased with the experience and have no improvements to suggest at this time.

Tatsuya Ishihara
Project Manager
★★★★★

“They’re always willing to adapt quickly to our needs and help keep the project on track.”

The team is highly responsive and flexible, quickly adapting to our needs to keep the project on track. Clear, detailed annotation guidelines help them deliver accurate results faster.

Park Ji-Ho
Director
★★★★★

“Communication with the team is smooth, clear, and effortless.”

We chose Smart Annotahub for its expertise, openness to new ideas, and strong interest in autonomous vehicles. Their team provides consistent cuboid and polygon annotation for our growing image dataset, with responsive communication, attentive project management, and reliable quality assurance. We’re very pleased with the collaboration and look forward to continuing our work together.

Matthew Milner
Director of Engineering

Start with a free pilot

Tell us about your data and requirements. We'll return an annotated sample with a precise quote, usually within a few working days.



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    Mobility and Autonomous Systems FAQs

    Can you label multi-sensor driving data?

    Yes. We annotate camera, LiDAR, and radar together and keep object IDs consistent across sensors and frames using your calibration files.

    How do you handle rare edge cases?

    Edge cases such as unusual vehicles, construction zones, or heavy occlusion are escalated, documented, and added to the guidelines so every annotator treats them the same way.

    Which formats do you deliver?

    We export to KITTI, nuScenes, COCO, or your custom schema, and can work directly inside your annotation platform.

    Can you scale for fleet data volumes?

    Yes. Teams scale with the same QA process, so quality stays stable as volume grows.