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Improve autonomous vehicles beyond the test track

Prepare your autonomous system for diverse road conditions using data annotation tools and specialists who understand real-world complexity.

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Why Uber AI Solutions for autonomous vehicles (AV)?

Accelerate data readiness across your autonomous driving system by leveraging Uber's automotive AI heritage and decade of machine-learning (ML) experience solving AV edge cases.

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Accelerate AV development

Strengthen AI precision in complex environments and varying regulatory climates with diverse, real-world driving datasets, multi-sensor labeling tools, and advanced testing frameworks.

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Consult with domain specialists

Engage program managers who can partner with your ML and AV engineers to establish project goals, create labeling guidelines, and monitor edge cases, and work with skilled annotators to perform high-fidelity annotation.

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Scale operations with your roadmap

Expand your labeling capacity and efficiency over the long-term as your AV program evolves, with comprehensive support across tools, workflows, specialists, and global markets.

“
Uber AI Solutions is a force multiplier and extension of our team that is critical to delivering a safe, reliable ML-based system.

’’

Farshid Moussavi

Head of Perception, Glydways
Read the story

Turn complex real-world data into high-quality learning signals for your models

Expand edge-case coverage

Equip your AV, computer vision (CV), and vision-language-action (VLA) models for noisy scenarios, object detection, and scene understanding with L2 and L3+ data sets and collection via dashcam.

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Reduce uncertainty using multi-sensor tools

Annotate LiDAR, RGBD, camera, radar, video, and mapping data with multi-sensor labeling and 3D point cloud labeling (cuboids, keypoints, polygons, polylines, segmentation).

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Improve the data behind AV decisions

Use AV-specific workflows, expert review, quality controls, and continuously updated labeling guidelines and workflows to produce consistent data as scenarios change.

Autonomous car with sensors drives in city traffic beside a cyclist in the bike lane during daylight.

Frequently asked questions

What automotive AI data formats can Uber AI Solutions (UAIS) support?

Uber AI Solutions supports AI data operations across the sensor modalities used in autonomous driving, CV, and VLA models, including camera, LiDAR, radar, video, and other multimodal datasets. We also use perception labeling techniques to do mapping labeling, such as polylines and polygons on road edges and lane lines in the point cloud, and frame-by-frame 2D video enrichment to provide complex scene reasoning.

Does Uber AI Solutions build autonomous driving software or AI models?

No. Uber AI Solutions does not build autonomous vehicles, perception software, or autonomy stacks. Your engineering teams remain responsible for model architecture, training, and deployment. UAIS supports those efforts by providing managed AI data operations that help improve model readiness.

When should an automotive AI team engage Uber AI Solutions?

Engineers turn to Uber AI Solutions in the early stage AI development process. Our program managers can consult with your team to help stand up the data services operation required to align with your project goals.

Let’s build better AI together

Tell us about your AV project. We'll show you the data that gets you there.

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