The startup develops display modules and spatial recognition software for augmented reality glasses, focusing on waveguides and spatial recognition engines. Their technology enables real-time recognition of environmental data and human movement, enhancing user interaction in augmented reality applications.
Funding
$44.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
GIFounders
Product
Problem
Current augmented reality (AR) glasses often suffer from limited field of view, bulky form factors, and inaccurate spatial understanding, hindering immersive and practical user experiences. Existing spatial recognition software struggles with real-time environmental data processing and precise human movement tracking, leading to suboptimal AR interactions.
Solution
Cellid develops advanced display modules and spatial recognition software designed to overcome the limitations of current AR technology. Their waveguide-based display modules offer a wider field of view and improved image clarity within a compact form factor suitable for lightweight AR glasses. The company's spatial recognition engine utilizes sensor fusion and machine learning to enable real-time 3D mapping, object recognition, and precise tracking of user gestures and movements. This combination of hardware and software aims to create more natural and intuitive AR experiences.
Target Audience
The primary target audience includes manufacturers of augmented reality glasses, enterprise solution providers developing AR applications, and researchers in the fields of computer vision and human-computer interaction.
Features
- Waveguide-based display modules for enhanced field of view and image quality
- Compact and lightweight design suitable for comfortable AR glasses
- Real-time 3D mapping and environmental understanding
- Precise human movement and gesture tracking
- Sensor fusion algorithms for robust spatial awareness
- Machine learning-powered object recognition