Active Intelligence’s ASTRA™ Anomaly Detection Solution Captures Global Attention

by | Products, Security

Active Intelligence, innovator of anomaly detection software for physical security and business intelligence applications, is building on the momentum of its successful official launch its ASTRA™ Autonomous Video Anomaly Detection solution by demonstrating how it has the unique ability to detect any anomalous activity in a video feed without the restrictions of conventional rules-based video analytics systems.

“The global reaction to ASTRA has been even better than we anticipated, with inquiries coming from a wide range of private business and public organizations,”said Ken LaMarca, CEO, Active Intelligence.

To further validate ASTRA’s effectiveness, Active Intelligence is offering a free 60 day trial to qualified users. “The best way for us to provide proof of performance is to let prospective customers take ASTRA for a test run on their own video system,” said LaMarca. “There have been so many claims made about video analytics by so many companies over the years, we want to definitively prove to potential customers that ASTRA delivers on its promise.”

Active Intelligence’s ASTRA takes a modern approach to video security, detecting both known and unknown threats by identifying statistical anomalies in video feeds. The software, powered by AI and Machine Learning algorithms, first learns what is normal in a specific camera’s field of view over a short period of time, and then detects abnormalities and alerts security operators when an anomaly is present.

Unlike conventional rules-based video analytics, ASTRA’s anomaly detection offers infinite detection capabilities, including events like a person in distress, physical violence, fire and smoke, pedestrians walking in front of moving vehicles, theft, vandalism, traffic jams, wrong way driving, and much more. The unlimited detection capabilities also make ASTRA ideally suited for a wide range of commercial and industrial business intelligence applications.

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