Edgify has developed a solution that allows companies to train complete deep-learning and machine-learning models directly on their own edge devices, mitigating the need for any data transfer to the cloud while also providing near-perfect accuracy every time, without the need to retrain on a server or the cloud.
Edgifys technology enables any connected device to interpret vast amounts of data generated at the edge, train a complete AI model locally, and share that learning across an entire network of similar devices, thereby training them all to identify unique aspects of a given object for use in computer vision, natural language processing, voice recognition, and any other form of artificial intelligence. Its framework can train artificial intelligence on a network of edge devices including MRI machines, connected cars, checkout lanes, mobile devices, and anything that has a CPU, GPU, or NPU.
Due to the continuous and distributed learning at the edge on data generated locally, the accuracy of an AI model trained on an Edgify Framework is averaged at 99.98% and never decreases. This helps to reduce the risks, costs, and time associated with transferring sensitive data to or from an external server and effectively eliminates the need for a cloud-based learning infrastructure.