VAYAVISION
Date | Investors | Amount | Round |
---|---|---|---|
- | N/A | - | |
$1.2m | Seed | ||
$8.0m | Seed | ||
€2.4m | Grant | ||
* | €2.5m | Grant | |
N/A | Acquisition | ||
Total Funding | €13.2m |
Recent News about VAYAVISION
EditVAYAVISION is a pioneering company in the autonomous vehicle (AV) industry, specializing in advanced perception technology. The company leverages artificial intelligence (AI) and computer vision to create highly accurate 3D environmental models. By fusing raw data from radar, lidar, and cameras, VAYAVISION enhances the perception capabilities of autonomous vehicles, enabling them to detect and classify objects with remarkable precision.
The core technology involves "raw data fusion," where data from different sensors are combined and processed to produce high-definition (HD) 3D models. This process includes upsampling, which means converting low-resolution data into high-resolution images. The result is an HD RGBd model that provides detailed information about the size, shape, and speed of surrounding objects, even those not present in the training data set.
VAYAVISION's technology is designed to be cost-effective, requiring only low-cost, low-resolution sensors to deliver reliable environmental perception. This makes it an attractive solution for AV manufacturers looking to enhance safety and performance without incurring high costs. The system also boasts inherent functional safety, meaning it can detect objects and potential dangers even if a sensor malfunctions.
The company primarily serves clients in the autonomous vehicle market, including automotive manufacturers and technology firms developing self-driving cars. VAYAVISION's business model revolves around selling its perception technology and software solutions to these clients, generating revenue through licensing fees and long-term contracts.
In summary, VAYAVISION is at the forefront of AV perception technology, offering a cost-effective, highly accurate solution that enhances the safety and reliability of autonomous vehicles.
Keywords: Autonomous Vehicles, Perception Technology, AI, Computer Vision, Raw Data Fusion, Lidar, Radar, Camera, 3D Models, Cost-Effective.