The startup develops AI-driven video surveillance systems that utilize real-time threat detection algorithms to identify life-threatening situations. By automating security alerts to personnel and authorities, the system enhances response times and improves safety for public and private entities.
Funding
$640K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
SFounders
Product
Problem
Existing video surveillance systems often require constant human monitoring to identify potential threats, leading to delayed response times and overlooking critical events. Traditional systems also lack the ability to proactively identify and alert personnel to potentially dangerous situations in real-time.
Solution
SecurifAI offers an AI-powered video analytics platform that automates threat detection and enhances security across various sectors. The system analyzes video feeds from existing CCTV cameras and DVRs in real-time, using deep learning algorithms to identify abnormal events, unattended objects, and safety violations. By automatically generating alerts for dispatchers and security personnel, SecurifAI enables faster response times and proactive intervention in potentially life-threatening situations. The platform is camera-agnostic and integrates seamlessly with existing ICT infrastructure, providing a cost-effective upgrade to conventional surveillance systems.
Target Audience
SecurifAI serves first responders, governments, city services, and private sector entities such as security companies, schools, and banks seeking to enhance safety and security through intelligent video surveillance.
Features
- Abnormal event detection using deep convolutional neural networks and support vector machines
- Abandoned object identification using background subtraction, motion tracking, and convolutional neural networks
- Real-time face detection and recognition, even with a single training photo per subject
- Facial expression recognition to detect anger, disgust, and other emotions that may precede criminal activity
- Contactless heart rate estimation to monitor stress levels and identify potential suspects
- Pedestrian and car detection and tracking using deep single-stage convolutional architectures and Siamese neural networks
- Customizable alerts and reporting through a back-office application and dedicated smartphone app
- Integration with Power BI and other business intelligence tools for extended analytics