Edgify completed a seed funding round of $6.5 million from Octopus Ventures, Mangrove Capital Partners

Edgify, a London, UL-based software developer of AI training frameworks, announced raising a $6.5m seed funding round.

The money was raised from investors including Octopus Ventures and Mangrove Capital Partners. Mangrove partner Hans-Jürgen Schmitz will join Edgify’s Board.

Edgify, founded in 2015 by CEO Ofri Ben-Porat and Nadav Israel, developed a piece of technology which enables any connected device - known as ‘edge devices’ - to interpret vast amounts of data generated at the edge, train a complete AI model locally, and proceed to share that learning across an entire network of similar devices, thereby training them all to identify unique aspects of a given object for use of computer vision, NLP, voice recognition and any other form of AI.

Edgify’s framework can train AI on a network of edge devices ranging from 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 per cent 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.

Edgify’s technology is already being used in supermarkets. Self-checkout machines are able to distinguish between barcode-less groceries before sharing the acquired knowledge or model across a distributed yet collaborative framework of point of sale machines, leading to faster, more accurate and low-touch checkouts.

In addition to the retail industry, Edgify is also in the process of deploying its Framework for the Medical and for the Automotive industries. Using the Edgify Framework to train AI models for pathologies in chest X Rays for medical, and to identify spare parts in the automotive industry.