Agnostic Vendor Data Forms for Real-Time Mesh Integration

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Solution Overview

Problem

The global distribution industry faces challenges in distribution management, supply chain complexities, inventory control, SKU management, compliance issues, and evolving consumer expectations due to divergent data formats, data fragmentation, inefficient data processing, and security concerns, which hinder efficiency and customer experience.

Innovation Solution

Implementing agnostic data formats (ADFs) using AI and ML technologies to manage diverse vendor data structures, coupled with a Single Pane of Glass (SPoG) and Real-Time Data Mesh (RTDM) for real-time data availability and integration, enhancing supply chain visibility, inventory management, and compliance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional ERP systems are used to manage vendor data, then data security and compliance are maintained, but data fragmentation and integration capabilities are limited

Engineering Contradiction:

Improvedata securityVSAvoiddata integration complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary data integration layer that sits between traditional ERP systems and the distribution platform. This layer uses APIs and data normalization techniques to bridge disparate vendor data formats without compromising the security of underlying ERP systems while enabling seamless data flow and integration across the platform.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent segments data management into modular components: data ingestion modules that handle vendor-specific formats, normalization modules that standardize data structures, and integration modules that connect to ERP systems. This segmentation allows each component to be optimized independently while maintaining overall system security and integration capabilities.

Inventive Principle:

Principle #1Segmentation

2Manufacturing precision

If bespoke automated systems are developed for each vendor, then vendor-specific data formats are handled accurately, but development time and costs increase substantially

Engineering Contradiction:

Improvedata format accuracyVSAvoidvendor onboarding time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent implements a universal data normalization framework that can handle multiple vendor-specific data formats through a single standardized interface. The system includes configurable data mapping templates and AI-driven format recognition that automatically adapt to new vendor formats without requiring bespoke development, thereby maintaining data accuracy while dramatically reducing onboarding time.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent employs dynamic parameter adjustment in its data processing engine, which automatically detects and adapts to different vendor data formats by modifying processing parameters rather than requiring custom system development. This allows the same core system to accurately handle diverse formats from different vendors while maintaining consistent processing speeds.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If conventional data processing systems are used, then existing infrastructure is maintained, but efficient handling of diverse vendor data formats is achieved

Engineering Contradiction:

Improvedata processing efficiencyVSAvoidsystem architecture complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces traditional mechanical data processing approaches with AI and machine learning-based systems that automatically recognize, interpret, and normalize vendor data formats. This substitution enables efficient processing of diverse formats without proportionally increasing system complexity, as the AI systems adapt to new formats through learning rather than requiring manual configuration of complex processing rules.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20260004320A1Systems and methods for managing agnostic data forms for vendors

Publication Date: 2026.01.01 INGRAM MICRO INC

AI summary

System and methods are provided for achieving data standardization and normalization through an Agnostic Data Format (ADF) architecture. ADFs systems and processes provide a transformative bridge, enabling disparate data sources to converge into a unified and standardized format within the Real-Time Data Mesh (RTDM) framework, This dynamic process utilizes Artificial Intelligence (AI) and Machine Learning (ML) algorithms to interpret and align diverse data, attributes, The ADF management system, integrated into a dynamic event-driven architecture, allows vendors to interact with RTDM by translating and standardizing their data. The synchronized data, integrates canonically, incorporating real-time updates and collaborative decision-making across the distribution platform. This innovative approach enhances operational efficiency, enables data-driven decision-making, and provides users improved ability to use data within the distribution ecosystem.