Cloud Data Integration Platform for Enterprise Resource Forecasting

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Enterprises face challenges in effectively managing finite resources and providing seamless communication between operational software platforms, leading to laborious and time-consuming data extraction and integration processes that hinder efficient decision-making.

Innovation Solution

A cloud-based platform utilizing AI and machine learning techniques integrates diverse data sources, enabling real-time data accessibility and forecasting, with features like AI virtual assistants and chatbots for personalized insights and resource allocation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If data is extracted and integrated manually from various isolated systems, then data can be combined to generate analytical dashboards, but the process becomes laborious and time-consuming

Engineering Contradiction:

Improvedata integration accuracyVSAvoidtime for data extraction and integration

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical data extraction and integration processes with automated computer-based systems. The system automatically extracts data from multiple isolated operational systems, transforms it through standardized protocols, and integrates it into unified analytical dashboards without human intervention, thereby eliminating the laborious and time-consuming nature of manual data processing while maintaining integration accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If multiple isolated operational software platforms are used, then specific operational functions can be performed, but seamless communication between platforms is lacking

Engineering Contradiction:

Improveoperational software functionalityVSAvoidcommunication between platforms

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The patent introduces a centralized data integration platform that acts as an intermediary between multiple isolated operational software platforms. This intermediary system establishes standardized communication protocols and data exchange formats, enabling seamless information flow between previously siloed systems while preserving each platform's operational independence and functionality.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If comprehensive specialized software is implemented, then data management efficiency can be improved, but system complexity increases

Engineering Contradiction:

Improvedata management efficiencyVSAvoidsoftware system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements a universal data integration platform that performs multiple functions including data extraction, transformation, loading, validation, and visualization within a single system. This multi-functional approach consolidates what would otherwise require multiple separate specialized software tools, thereby improving data management efficiency while actually reducing overall system complexity through consolidation.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250292271A1Systems and Methods for Data Sourcing, Integration, Distribution, and Forecasting for Enterprises

Publication Date: 2025.09.18 SECOND HARVEST FOOD BANK OF NORTHWEST NC

AI summary

Computer-implemented methods and platforms for data sourcing, integration, distribution, and forecasting for enterprises are provided. The methods and systems provided herein uses cloud computing infrastructure, to collect data from a plurality of systems to generate an indexed data store and to forecast a resource availability based on data in the indexed data store. The methods and systems provided herein can utilize advance artificial intelligence (AI) and machine learning (ML) techniques, coupled with robust data warehousing capabilities.