Making Robbery More Difficult With AI

Bengaluru: We’ve all watched the movie scene where the bank teller attempts to reach a silent alarm while a robbery takes place. Deep Science AI is about to make that scenario a thing of the past with its AI Surveillance (AIS) platform for businesses. AIS leverages the latest in deep learning to identify people concealing their faces, firearms, or intruders after-hours or where they shouldn’t be, and alerts a security analyst monitoring remotely. The platform allows the analyst to monitor 500 or more surveillance feeds at once, making remote surveillance monitoring cost-effective for most businesses for the first time.
“Smart visual sensors with low false positives haven’t been possible until now,” says board member and former ADT President Mike Snyder. “This new capability fills a large ability gap in the physical security marketplace,” he added.
“Small business retail owners in high crime areas are robbed as often as once every six weeks. We think AIS can not only provide better active protection for these customers, but also act as a new deterrent,” says founder and CEO Sean Huver. “Criminals like to rob easy targets. They’ll skip a business if they know someone is watching and the response will be immediate,” he added.
There are other AI applications in the home surveillance market being developed by companies such as Camio and OWLR, but AIS is the first platform to be aimed at armed threat detection, ranging from robberies to active shooter events.
Most businesses that currently use remote surveillance monitoring are either large companies protecting corporate campus property, or have high priced and vulnerable inventory, such as car dealerships. AIS will cost a fraction of these human-only monitoring solutions at $2 per camera per day.



Deep Science AI was founded in 2016 by Dr. Sean Huver, a research scientist and veteran of numerous DARPA projects. Mike Snyder, former President and COO of ADT, joined the board of directors in February 2017.

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