TASER Makes Two Acquisitions to Create "Axon AI"
TASER acquired Dextro, Inc, the first computer-vision and deep learning system to make the visual contents in video searchable in real time. Agencies and departments will have the ability to quickly isolate and analyze the most important seconds of footage from massive amounts of video data. This acquisition will form the technology backbone of the new Axon AI platform.
The company also acquired from Fossil Group, Inc. the computer vision team that was part of Fossil Group's acquisition of
The Axon network connects devices, apps and people for more than half of the nation's major city police agencies. Axon AI will extend TASER's research and development efforts and significantly expand the capabilities of the Axon network. These investments in artificial intelligence will have a transformative impact on Axon products by making workflows smarter including deep data analysis on the more than 5.2 petabytes of customer data hosted across the Axon Network.
Axon AI will transform key customer workflows using computer vision and natural language processing along with machine learning techniques. The addition of artificial intelligence to Axon's upcoming records management system (RMS) has the potential to automate the collection and analysis of virtually all information in public safety while extracting key insights never before possible. The benefits of this groundbreaking technology leads to a future of hands-free reporting and real time intel in the field.
"We believe it's time for video data to move to the center of public safety records systems, with far richer and more transparent information than historic text-only systems," said
"Dextro has built a highly advanced video analytics technology driven by machine learning, which requires high volumes of video training data," said
To learn more about how TASER is bringing AI to law enforcement, join
Dextro makes videos discoverable and searchable using machine learning. In the two years since their founding they have poured countless research hours into computer vision, developing algorithms that can analyze the audiovisual contents of video footage in real time in order to provide meaningful data. Their experience ranges from analyses of web video content for marketers and video curators to real-time analysis of security footage and automatic categorization of video evidence for law enforcement.
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