[Data] Food Industry (Manufacturing/Retail/Wholesale)

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last updated：Feb 20, 2023

MatrixFlow

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Utilizing MatrixFlow! Methods for improving accuracy and efficiency in business using AI, along with case studies of solutions!

Since the COVID-19 pandemic, a major transformation has occurred in the food industry. As a result, the food industry faces various challenges common to manufacturing, wholesale, and retail sectors, including "low profit margins and growth rates," "rising costs of raw materials, labor, and logistics," "increased quality standards," "efficiency in inventory management (reducing food waste)," and "responding to complex sales channels from procurement to distribution." Additionally, in recent years, even non-experts can utilize IT technologies such as AI, making it possible to address the above challenges more efficiently. This document introduces methods for solving challenges faced by food companies using AI. [Contents (partial)] ■ Challenges in the food industry ■ Solutions to challenges in the food industry using AI ■ Current status and key points of AI utilization *For more details, please refer to the PDF document or feel free to contact us.

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【Other Published Content】 ■Challenges in the Food Industry 　・Challenges in Food Manufacturing 　・Challenges in Food Retail 　・Challenges in Food Wholesale ■Solutions to Food Industry Challenges Using AI 　・Examples of solving food industry challenges using MatrixFlow 　・Examples of solving food industry challenges using AI 　・Introduction to MatrixFlow: No programming required. Build AI tailored to specific challenges just by selecting options 　・Why solutions utilizing AI and MatrixFlow are effective 　・AI demand forecasting that can be done on-site ■Current Status and Key Points of AI Utilization 　・With AutoML, AI can be implemented quickly and on a small scale 　・Understand what contributes to sales/customer numbers 　Deployment of advanced measures utilizing XAI (Explainable AI) *For more details, please refer to the PDF document or feel free to contact us.