ZAC

ZAC (Z Advanced Computing, Inc.) is a 3D image recognition and search platform based on Cognitive Explainable-AI (CXAI). According to the vendor, ZAC's platform enables detailed 3D image recognition, allowing users to detect fine details in images taken at various camera angles. The technology aims to overcome the limitations of existing AI technologies, which may struggle to recognize details beyond generic categories or classifications. ZAC applies Cognitive Explainable-AI to machine learning, which, according to the vendor, allows the technology to learn and detect fine details where interesting features usually reside. Unlike other AI technologies based on neural networks, ZAC's CXAI approach is said to require fewer training samples and produce more accurate and detailed outputs.

ZAC's horizontal platform offers tools and APIs that, according to the vendor, enable a wide variety of vertical applications and industries to take advantage of its efficient, detailed, and accurate recognition and search capabilities. Some of the industries that the vendor suggests can benefit from ZAC's technology include medical imaging/diagnosis, e-commerce/retail, search engine and ad networks, smart home/appliance, and defect and anomaly detection for manufacturing and construction.

The vendor claims that ZAC's solution for pathology assists physicians and pathologists in analyzing complex pathological images. According to the vendor, the solution automates the analysis of pathological images, helping pathologists make more accurate descriptions and conclusions. The vendor further suggests that ZAC's technology in medical imaging provides higher accuracy, reliability, and reproducibility compared to existing methods, while requiring a low number of training samples and less computation resources.

ZAC's technology also enables search by image in e-commerce, providing users with a more intuitive and efficient way to find products, according to the vendor. The platform's image recognition capabilities allow users to search for products based on their visual appearance rather than relying solely on text-based search queries. The vendor claims that this feature enhances the user experience, increases customer engagement, and improves conversion rates in the e-commerce industry.

The vendor states that ZAC's platform requires only a few training samples and uses reusable, modular, cumulative, and scalable learning methods, which are claimed to enable faster and more efficient learning, reducing the time and resources required for training. They further claim that ZAC's CXAI approach produces more accurate and detailed outputs compared to other AI technologies based on neural networks, ensuring that the platform can detect fine details in images and provide users with reliable and precise results.

According to the vendor, ZAC's technology is suitable for companies of all sizes, from startups to large enterprises. They suggest that it can help enhance workflow and throughput in the pathology field by automating the analysis of pathological images, resulting in improved efficiency and productivity for pathologists. Additionally, the vendor claims that ZAC's technology can improve the user experience by accurately recognizing and matching fine details in images, making it easier and more enjoyable for customers to discover products in applications such as search by image in e-commerce.