Kognition
Kognition delivers cutting-edge security technology powered by AI that ensures consistent and proactive threat detection, all while being significantly more cost-effective than traditional security measures. By integrating effortlessly with current systems, we enable organizations to identify potential risks—such as the display of weapons or the formation of crowds—and alert security teams regarding unauthorized individuals and VIPs. This innovative solution not only minimizes IT costs but also decreases the reliance on additional security staff, thereby improving the efficiency of incident responses. Additionally, Kognition provides comprehensive security reporting and enhanced visibility across various sectors, including K-12 education, commercial real estate, and heavily regulated industries. Ultimately, our technology empowers organizations to create safer environments, making security more accessible and manageable than ever before.
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Athena Security
Athena Security: Protecting People with Purpose
Athena Security is an Austin-based physical security technology company driven by a singular, life-saving mission: to help save lives. Founded by the veteran leadership team behind Revel Systems—Michael Green, Lisa Falzone, and Chris Ciabarra—Athena has redefined entryway safety by replacing outdated, manual screening processes with a proactive, AI-driven digital framework.
At Athena, we believe that security is a shared responsibility. Human fatigue is the greatest vulnerability in any security posture; therefore, our philosophy is to automate the mundane so humans can focus on the critical. By digitizing the screening process, we ensure that every visitor is screened according to DHS Best Practices, providing a consistent, high-level layer of protection that never gets tired, distracted, or overwhelmed.
The "iPad-Simple" Advantage
We believe that the most sophisticated technology in the world is useless if it’s too hard to use. To ensure our products are accessible to every security officer, Athena utilizes Apple iPads as the primary user interface for our entire product line. Unmatched Simplicity: If a guard can use a smartphone, they can master Athena in minutes. This reduces training costs and eliminates operator error.
Edge AI Power: We harness the high-performance Apple Silicon within the iPad to run our proprietary AI models locally. This means threat detection happens in milliseconds, even if the facility's internet goes down Athena stays up thanks to the power of the iPad.
Apollo 500 Weapons Detection: A high-throughput walk-through system that screens up to 2,500 people per hour. It intelligently ignores phones and keys while instantly flagging firearms and explosives.
AI-Assisted X-Ray Software: A hardware-agnostic AI layer for baggage scanners that automatically identifies weapons and disassembled drone parts.
Healthcare Visitor Management (VMS): An iPad-based kiosk system
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Oz Liveness
Oz Liveness stands at the forefront of facial recognition and authentication technology, utilized by both private and public sectors globally to mitigate the threat of biometric fraud. By effectively countering deepfake and spoofing attempts, it safeguards identities with precision.
The software employs sophisticated algorithms engineered to identify various types of biometric spoofing, including 3D and 2D masks, as well as images and videos played on devices such as iPads and laptops.
Endorsed by the rigorous ISO30107 certification, our technology assures organizations that they can authenticate a genuine individual within moments. This accreditation not only enhances security but also significantly reduces compliance and fraud risks for users. Furthermore, the continued evolution of our capabilities ensures that we stay ahead of emerging threats in the biometric landscape.
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Amazon Rekognition
Amazon Rekognition streamlines the process of incorporating image and video analysis into applications by leveraging robust, scalable deep learning technologies, which require no prior machine learning expertise from users. This advanced tool is capable of detecting a wide array of elements, including objects, people, text, scenes, and activities in both images and videos, as well as identifying inappropriate content. Additionally, it provides accurate facial analysis and search capabilities, making it suitable for various applications such as user authentication, crowd surveillance, and enhancing public safety measures.
Furthermore, the Amazon Rekognition Custom Labels feature empowers businesses to identify specific objects and scenes in images that align with their unique operational needs. For example, a company could design a model to recognize distinct machine parts on an assembly line or monitor plant health effectively. One of the standout features of Amazon Rekognition Custom Labels is its ability to manage the intricacies of model development, allowing users with no machine learning background to successfully implement this technology. This accessibility broadens the potential for diverse industries to leverage the advantages of image analysis while avoiding the steep learning curve typically linked to machine learning processes. As a result, organizations can innovate and optimize their operations with greater ease and efficiency.
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