AnywayLabs.ai provides a platform for configuring, generating, and sharing production-ready synthetic computer vision datasets. The company specializes in photorealistic synthetic data for automotive, industrial, and retail applications, with datasets like ADAS Detection and Driver Monitoring System. Their platform enables users to configure a dataset in about five minutes and receive a shareable spec card, with performance metrics validated against real-world data.
Funding
Funding not disclosed
Founders
Product
Problem
Training robust computer vision models requires large, accurately annotated datasets, but collecting and labeling real-world footage is time-consuming, expensive, and often fails to cover edge cases. This is especially challenging in specialized domains like trucking fleets, industrial safety, and retail security, where real-world data is scarce, privacy-sensitive, or hazardous to capture.
Solution
AnywayLabs.ai offers a platform for configuring and generating photorealistic synthetic datasets tailored to specific computer vision tasks. Users can define their dataset parameters in about five minutes and receive a shareable spec card, streamlining the dataset creation workflow. The company provides production-ready datasets, such as ADAS Detection for multi-FOV fisheye truck cameras and Driver Monitoring System for cabin-view behavior analysis, all 100% synthetically generated. Their datasets are validated against real-world held-out images, with performance metrics like mAP@0.5 and precision provided, and they recommend mixing 10–25% real images for production deployments.
Target Audience
Primary customers are computer vision engineers and ML teams in automotive, industrial safety, and retail security sectors who need high-quality, scalable training data for object detection models.
Features
- 100% synthetically generated images with no real-world footage used, ensuring privacy and scalability
- Pre-built datasets for automotive (ADAS, DMS), industrial anomaly detection, and retail security use cases
- Detailed per-class performance metrics (AP@0.5, AP@0.5:0.95, precision, recall) validated on real-world data
- Annotation format in YOLO with high-resolution (1920x1080) images and commercial licensing
- Custom dataset variants and sample access available with typical turnaround of two business days