ADAS Data Annotation Platform
By rProcess
Optimized not just for speed - but for Truth
Why YOLOViz
Enabling Large Scale Perception Data - Without Limits
Engineered to process massive multimodal datasets without performance bottlenecks, browser limitations, or workflow interruptions.
Handles 3000+ Frames & Ultra-Dense LiDAR Point Clouds
Supports 3000+ frame sequences and LiDAR point clouds exceeding 50 million points per frame.
Data Integrity From Ingestion To Ground Truth Generation
Maintaining raw data integrity without compromising dataset continuity, consistency, or annotation accuracy throughout the entire workflow.
How YOLOViz Stands Apart
| Capability | YOLOViz by rProcess | Cloud Platforms |
|---|---|---|
| On-Prem / Air-Gapped Deployment |
Fully supported
|
Not supported
|
| Infrastructure |
On-prem, data centers & VDI
|
Internet-dependent; data leaves network
|
| Data Security |
Air-gap capable
|
Data uploaded to third-party servers
|
| Memory & GPU Processing |
Direct GPU memory mapping
|
Browser bottlenecks with heavy datasets
|
| LiDAR & 3D Performance |
Fluid across millions of points
|
Lag with large-scale sequences
|
| Compute Power |
Enterprise GPU-powered processing
|
Limited by local hardware & browsers
|
| Data Pipeline & Format Support |
Native ADTF, ROS Bag & PCD
|
Requires format conversion
|
| Multi-Sensor Fusion |
Full support
|
Limited support
|
| AI Pre-Labeling & Automation |
Full support
|
Full support
|
| Safety-Critical QA Pipeline |
Multi-tier safety-critical QA
|
Standard QA workflows
|
| ADAS Workforce & Services |
Platform + expert ADAS workforce
|
Platform-focused only
|
| Best For | ADAS camera, radar, full-stack AV datasets | Generic ML annotation use cases |
See YOLOViz in Action
Experience enterprise-grade visualization, validation, and quality control workflows engineered for next-generation autonomous driving and physical AI systems.