A manufacturing & distribution company dealing with volatile cheese prices faced difficulties in making informed market investments due to the highly manual process of gathering, researching, and analyzing data. This inefficiency resulted in inconsistent market condition assessments and delayed decision-making, particularly as prices fluctuated daily.

A comprehensive solution was developed to streamline market research and enhance forecasting accuracy. The solution centralized data from multiple sources, including StoneX, Ever.Ag, UDM, and BlueYonder. A Large Language Model (LLM) was implemented to process and extract sentiment from over 3,300 PDF reports, organizing insights into a structured format. Machine learning models were trained to predict market trends with 60-80% accuracy, while Shapley Values provided transparency in predictions. A user interface was created for data access, with visualizations aiding analysts in identifying new patterns and factors influencing market trends.

Enhanced Market Insights: Centralized data and AI-driven analysis improved forecast accuracy and insights.

Improved Decision-Making: AI models provided reliable market trend predictions, improving investment strategies.

Increased Efficiency: Automation of research and analysis reduced time spent on manual processes, enabling faster decision-making.

Transparency in Predictions: Shapley Values ensured clarity in the AI models’ decision-making process, building trust in the predictions.