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DateInvestorsAmountRound
-investor

€0.0

round
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€0.0

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$15.0m

Series A
Total Funding000k

Financials

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Revenues, earnings & profits over time
USD2020202120222023
Revenues0000000000000000
% growth-27 %18 %-
EBITDA0000000000000000
Profit0000000000000000
EV0000000000000000
EV / revenue00.0x00.0x00.0x00.0x
EV / EBITDA00.0x00.0x00.0x00.0x
R&D budget0000000000000000

Source: Dealroom estimates

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More about Viisights
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Viisights, established in 2015 by a team of seasoned entrepreneurs including Asaf Birenzvieg, Maya Scheffer, Menashe Rothschild, and Simon Polb, has positioned itself as a key player in the field of behavioral recognition analytics for video intelligence. The company's genesis is rooted in the extensive experience of its founders in artificial intelligence, deep learning, and computer vision, aiming to move beyond simple object detection to a more nuanced understanding of actions and events as they unfold.

The firm's core business revolves around its proprietary AI and deep learning technology, which analyzes real-time video streams to identify and predict specific human behaviors. This technology serves a diverse client base that includes municipalities aiming to create 'smart cities', large enterprises, educational campuses, and operators of critical infrastructure like transportation hubs. Viisights operates on a B2B model, providing its software solutions to these entities to enhance their existing security and operational frameworks. Its revenue is generated through the sale and licensing of its software, often integrated with existing video surveillance systems. The company has secured significant funding to fuel its growth, including a $10 million Series B round led by Impresa Pizzarotti and with participation from existing investor Charterhouse Capital Partners.

The flagship product, viisights Wise, is an AI-powered platform designed to autonomously detect and flag a wide array of activities without relying on facial recognition, thereby addressing privacy concerns. Its capabilities include identifying violent acts, spotting concealed or drawn weapons, and recognizing context-specific suspicious activities such as a person loitering in a restricted area. Furthermore, the system can monitor crowd behavior, track vehicle and traffic flow, and detect environmental hazards like fires or floods. This allows security personnel to shift from passive monitoring to proactive response, receiving real-time alerts for events that require immediate attention.

Keywords: behavioral recognition, video analytics, artificial intelligence, public safety, smart cities, security solutions, real-time intelligence, computer vision, situational awareness, incident detection

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