Abstract: Systems and methods are provided to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system uses a metadata-based data mapping template to match fields from one database system to the other. The system can generate and publish master data of a plurality of business entities.

Abstract: Systems and methods are provided for identifying a product in an image and outputting stock keeping units of the product. The system comprises three main components: a database server, a data analytics system and a standard dashboard. The database server contains real-time inventory images as well as historical images of each product type. The data analytics system is executed by a computer processor configured to apply a multi-head self-supervised learning-based classifier to detect product information captured by the image. The data analytics system is also configured to determine hierarchical classification categories for the product. The standard dashboard is configured to output a report regarding the product information.

Abstract: Systems and methods are provided to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system uses a data harmonization module to organize, classify, analyze and thus relate previously unrelated data stored in multiple databases and/or associated with different organizations. The system can generate and publish master data of a plurality of business entities.

Abstract: Systems and methods are provided to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system uses a data harmonization module to organize, classify, analyze and thus relate previously unrelated data stored in multiple databases and/or associated with different organizations. The system can generate and publish master data of a plurality of business entities.

Abstract: Systems and methods are provided to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system uses a metadata-based data mapping template to match fields from one database system to the other. The system can generate and publish master data of a plurality of business entities.

Abstract: Systems and methods employ knowledge distillation for efficient machine learning. Systems and methods integrate self-supervised learning, supervised learning, semi-supervised learning and active learning, each of which learning is executed in an iterative fashion. The system comprises three main components: a database server, a data analytics system and a standard dashboard. The database server contains real-time inventory images as well as historical images of each product type. The data analytics system is executed by a computer processor configured to apply a multi-head self-supervised learning-based deep neural network. The standard dashboard is configured to output a report regarding the object information.

Abstract: Systems and methods are provided for detecting an object region in an image and encrypting/decrypting a detected object region. The system comprises three main components: a database server, a data analytics system and a standard dashboard. The database server may further comprise a distributed database server and a key store database server. The data analytics system is executed by a computer processor configured to apply a multi-head self-supervised learning-based classifier to detect object information captured by the image. The data analytics system further comprise a privacy processing component that is configured to selectively encrypt the detected object using an encryption key following the advanced encryption standard with cipher block chaining mode (AES-CBC).

Abstract: Systems and methods are provided for identifying a product in an image and outputting stock keeping units of the product. The system comprises three main components: a database server, a data analytics system and a standard dashboard. The database server contains real-time inventory images as well as historical images of each product type. The data analytics system is executed by a computer processor configured to apply object detection and classification and deep learning algorithms to detect product information captured by the image. The data analytics system is also configured to determine hierarchical classification categories for the product. The standard dashboard is configured to output a report regarding the product information.

Abstract: The present disclosure describes a system and method for profiling and predicting customer behavior using machine learning. The system for profiling and predicting customer behavior uses all available signals from each individual customer across digital channels to build predictive artificial intelligence algorithms to create customer genome markers that predict the likelihood that specific customer will respond to digital actions.

Abstract: System and method of detecting friction in a website comprising a plurality of webpages and links includes a database sever, an application executed by a processor, and a management dashboard. The application extracts text data and web usage data from the website, segments the website into three funnel stages, identifies an anomaly in the web usage data, quantifies the impacts of the webpages and links, identifies the friction and the underlying root cause, and displays the friction in the management dashboard.

Abstract: Systems and methods are provided for identifying a product in an image and outputting stock keeping units of the product. The system comprises three main components: a database server, a data analytics system and a standard dashboard. The database server contains real-time inventory images as well as historical images of each product type. The data analytics system is executed by a computer processor configured to apply a multi-head self-supervised learning-based classifier to detect product information captured by the image. The data analytics system is also configured to determine hierarchical classification categories for the product. The standard dashboard is configured to output a report regarding the product information.

Abstract: Systems and methods are provided for identifying a product in an image and outputting stock keeping units of the product. The system comprises three main components: a database server, a data analytics system and a standard dashboard. The database server contains real-time inventory images as well as historical images of each product type. The data analytics system is executed by a computer processor configured to apply object detection and classification and deep learning algorithms to detect product information captured by the image. The data analytics system is also configured to determine hierarchical classification categories for the product. The standard dashboard is configured to output a report regarding the product information.

Abstract: The present disclosure describes a system and method for profiling and predicting customer behavior using machine learning. The system for profiling and predicting customer behavior uses all available signals from each individual customer across digital channels to build predictive artificial intelligence algorithms to create customer genome markers that predict the likelihood that specific customer will respond to digital actions.

Abstract: System and method of detecting friction in a website comprising a plurality of webpages and links includes a database sever, an application executed by a processor, and a management dashboard. The application extracts text data and web usage data from the website, segments the website into three funnel stages, identifies an anomaly in the web usage data, quantifies the impacts of the webpages and links, identifies the friction and the underlying root cause, and displays the friction in the management dashboard.

Abstract: Some embodiments are associated with a system and method for deep learning unsupervised anomaly detection in Internet of Things (IoT) sensor networks or manufacturing execution systems. The system and method use an ensemble of a plurality of generative adversarial networks for anomaly detection.

Abstract: The invention relates to systems and methods for automated insight curation and alerting. The system generates insights from time-series data at scale using unsupervised machine learning algorithms. The system can further automate the suggested actions by signaling the actuators or middleware which ultimately executes the action.

Abstract: Systems and methods are provided for insight automation from content data. The system generates insights from online and offline data at scale using unsupervised or supervised machine learning algorithms. The system can further generate insight at various levels for continuous evaluation and automated promotion.