Agblox, Inc.

Michael G Mcerlean

Spyros J Lazaris

Alex A Kurzhanskiy

Thomas N Blair

Tony Chiyung Lei

Craig I Forman

Leo Richard Jolicoeur

A data analytics platform is provided for forecasting future states of commodities and other assets, based on processing of both textual and numerical data sources. The platform includes a multi-layer machine learning-based model that extracts sentiment from textual data in a natural language processing engine, evaluates numerical data in a time-series analysis, and generates an initial forecast for the commodity or asset being analyzed. The platform includes multiple applications of neural networks to develop augmented forecasts from further analysis of relevant information as it is collected. These include commodity-specific neural networks designed to continually develop taxonomies used to process commodity sentiment, and applications of reinforcement learning, symbolic networks, and unsupervised meta learning to improve overall performance and accuracy of the forecasts generated.

Generative artificial intelligence-based agents using customized neural networks

Sentiment and rules-based equity analysis using customized neural networks in multi-layer, machine learning-based model

Growing community of inventors

SIOUX FALLS, SD, United States of America

Michael G Mcerlean