Home Challenge 22 Challenge 22 Startups-Synaplexus

Challenge 22 Startups-Synaplexus


Synaplexus deploys a network of smart cameras to enhance crowd management. Each camera will run deep learning algorithms (a class of machine learning algorithms that achieves better predictive performance) to analyse the crowd and detect or predict certain behaviours.

Deep Vision at The Edge

Synaplexus mission is to bring state of the art Deep Learning algorithms for computer vision to IoT Edge devices. Synaplexus aims to achieve this through targeting first the surveillance and crowd management segments of the video analytics market and then expands its scope to drones, robotics, automotive and smart cities domains.


Ahmed Khalil has over 18 years of experience in the wireless communications domain, which included designing and developing system software for mobile handsets for various multinational companies in Cairo, Egypt and Munich, Germany. Ahmed was also a senior manager at the Atmel Corp subsidiary of Microchip.

Ahmed Ezzat has eight years of experience in embedded systems development. He is an expert in IPv4 and IPv6 embedded design as well as TLS cipher suites. His designs have been deployed in devices used in commercial internet of things products such as Amazon’s Dash Button and Garmin’s forerunner fitness band.



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