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Top 50 Cmos Image Sensor in Africa
Discover the top 50 Cmos Image Sensor startups in Africa. Browse funding data, key metrics, and company insights. Average funding: $29.6M.
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SiLC Technologies
SiLC Technologies develops a coherent FMCW LiDAR vision sensor that provides high-resolution, 4D imaging data for vehicles and AI robots, enabling them to accurately classify objects in real-time. This technology addresses the need for enhanced machine perception in mobility, perimeter security, and industrial automation applications.
Funding: $50M+
Rough estimate of the amount of funding raised
Dragonfly Aerospace
Dragonfly Aerospace develops compact, high-performance imaging satellites and payloads that provide wide-spectrum Earth observation data for applications in agriculture and environmental monitoring. Their technology enables efficient deployment of satellite constellations, delivering timely and accurate information to support sustainable practices and informed decision-making.
PIxemantic
Pixemantic develops AI-powered image analysis software that automatically extracts insights from imaging sensor data. Their technology helps users interpret images more efficiently, enabling faster and more accurate decision-making.
Kipepeo Aerospace
Kipepeo Aerospace provides modular unmanned aerial systems with interchangeable payloads for photogrammetry, multispectral imaging, and LiDAR, combined with on‑board edge AI that generates georeferenced maps, NDVI indices, and object detections in real time. Processed data are synced to a secure cloud platform offering dashboards, GIS‑compatible exports, and RESTful API integration for agribusinesses, government agencies, and research institutions. The low‑cost, locally manufactured design meets African UAS regulations and reduces adoption barriers for precision farming, infrastructure monitoring, and security operations.
Imago Systems, Inc.
The startup develops a medical imaging platform that employs artificial intelligence to enhance pixel density patterns in images, such as mammograms, making subtle abnormalities visually distinct. This technology enables earlier detection of cancer and other tissue abnormalities, improving patient outcomes and overall health.
Funding: $3M+
Rough estimate of the amount of funding raised