Systems and methods for integrating real-time business insights

The system integrates AI and ML technologies to address real-time data integration challenges in distribution platforms, providing actionable insights and optimizing operations for smaller customers.

JP2026087522APending Publication Date: 2026-05-27INGRAM MICRO INC
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Patent Information

Authority / Receiving Office
JP · JP
Patent Type
Applications
Current Assignee / Owner
INGRAM MICRO INC
Filing Date
2025-11-15
Publication Date
2026-05-27

AI Technical Summary

Technical Problem

Conventional distribution platforms face challenges in obtaining real-time actionable insights due to siloed data, batch processing, data inconsistency, lack of advanced analytics, and insufficient support for smaller customers, leading to inefficient decision-making, inventory management, and operational fragmentation.

Method used

A system integrating AI and ML technologies to provide real-time data integration and analysis across customer, vendor, and reseller systems, using a single-pane-of-glass UI, real-time data mesh, and advanced analytics to generate actionable insights, with robust security measures.

Benefits of technology

Enables smaller customers to access comprehensive, real-time insights for informed decision-making, optimizing operations, improving inventory management, and enhancing customer experience without significant infrastructure investments.

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Abstract

We provide systems, methods, and devices that use artificial intelligence (AI) and machine learning (ML) technologies to ingest, integrate, and analyze data from multiple sources, delivering comprehensive and actionable insights in real time. [Solution] System 300 includes a single-pane-of-glass user interface (SPoG UI) that serves as the primary interface for the user, providing a unified view of data and insights from various modules within the system. The real-time data mesh (RTDM) module facilitates continuous data flow and harmonization, ensuring data consistency and accuracy across the platform. The advanced analytics and machine learning (AAML) module employs a predictive analytics engine, an anomaly detection engine, and a recommendation engine to generate insights and provide actionable recommendations.
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