Autonomous driving
AUTOMOTIVE & INTELLIGENT VEHICLES
Camera, LiDAR and linked sensor data for autonomous driving, ADAS and OEM perception teams.
AI DATA FOR REAL-WORLD INTELLIGENCE
Real-world AI.Production-ready data.
Data collection, 2D / 3D annotation, quality review and batch delivery for autonomous driving and computer vision.
Camera + LiDAR / KEYFRAME
3D Cuboid
Vehicle36
Pedestrian12
Cyclist4
Other6
2,000,000frames
Single-project delivery scale
Continuous frames and complex road scenes
300people
Specialist delivery team
Dedicated roles and consistent training
98.6%
On-time delivery rate
69 of 70 delivery batches on schedule
2D / 3D
Visual data tasks
Images, LiDAR and sensor associations
BUILT FOR AI TEAMS
Data services for your AI task
AI & computer vision
ALGORITHMS & APPLICATIONS
Image, video and text annotation for detection, segmentation, tracking and OCR.
Research & innovation
RESEARCH & INNOVATION
Data preparation and annotation for robotics, physical AI and academic research.
AUTOMOTIVE AI DATA
From road scenes to connected sensor data.
Organize camera, video and point-cloud data around perception tasks, with clear synchronization, annotation rules and delivery scope.
CAPABILITIES
Find the service your project needs.
From collection to annotation, define the task, agree on samples and set the review criteria.
01
DATA ANNOTATION
Data annotation
Turn model requirements into annotation rules. Align results through pilot work, review and rework.
02
DATA COLLECTION
Data collection
Plan around scene coverage, check quality in a pilot and define the batches and handover structure.
Support across the data workflow
Annotation platform
Connect tasks, rules, reviews and delivery records.
AI-assisted processing
Assess pre-annotation, cleaning and human review for each task.
HOW WE DELIVER
Align first. Deliver with a clear process.
Four stages connect initial requirements to handover. Explore the full workflow and sample records on the delivery page.
- 01
Scope & assessment
Define the task, data scope and deliverables.
- 02
Pilot & rule alignment
Align rules and scene coverage on a small batch.
- 03
Production & review
Work in batches and track issues and rework.
- 04
Acceptance & handover
Check the agreed scope and deliver data with records.
QUALITY IN EVERY STEP
Quality records accompany the data.
Make rule versions, review coverage and open issues clear, so every delivery can be checked.
CASE STUDIES
Three projects. A clearer view of the work.
Explore how each service approaches project scope, review and handover.
CASE STUDYAutomotive: connected sensor data
12 sequences · 1,200 synchronized keyframe groups
Explore scene groups, association rules and sample review.
Read case studyCASE STUDYCollection: a plan for scene coverage
120 planned clips · 20 seconds per clip
Explore scene targets, pilot checks and issue resolution.
Read case studyCASE STUDYAnnotation: align rules on a small batch
360 images · 4 classes · 1 pilot batch
Explore annotation boundaries, disagreements and review scope.
Read case studyExplore the key decisions behind each project, from scope and review records to delivery manifests.
GET IN TOUCH
Start with your data needs.
Share your project goal, data type and approximate scale to give the next discussion a clear starting point.
- 01
Project goal
Which model task or business use case?
- 02
Data scope
Do you have data, or need it collected?
- 03
Delivery needs
Preferred formats, review criteria and timeline.
Project information supports scoping and service assessment.
Tell us about your project
Share your goals, data volume and delivery requirements to help shape the discussion.