AI Data Tokenization for Single Source of Truth
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Solution Overview
Problem
The fragmentation of data across multiple sources of truth leads to complexity, inconsistency, and the need for manual workarounds, resulting in an inefficient and inconsistent user experience.
Innovation Solution
A system that tokenizes and categorizes data transactions using an AI algorithm to cull entity identifier data and other data from various communication blocks, placing it in a dynamic grid for division and extraction, and utilizing smart contracts to validate and store the data in decentralized nodes, creating a single source of truth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in multiple communication blocks and sources of truth, then data availability and redundancy are improved, but system complexity and data fragmentation increase
Solution Approach 1:
The patent introduces a data reconciliation service as an intermediary component that sits between multiple data sources and consumes. This service automatically reconciles data across different communication blocks and sources of truth, resolving conflicts and inconsistencies without requiring complex manual intervention. The intermediary handles the complexity of data fragmentation centrally, allowing the system to maintain multiple sources while avoiding the associated complexity.
Solution Approach 2:
The system implements self-service through automated data reconciliation processes that occur without manual intervention. The data reconciliation service automatically detects, resolves, and reconciles data inconsistencies across multiple sources, enabling the system to maintain data consistency autonomously. This reduces the need for complex manual workarounds and administrative overhead while preserving the benefits of multiple data sources.
2Quantity of substance
If multiple sources of truth are maintained, then data completeness and redundancy are improved, but data consistency and reconciliation effort worsen
Solution Approach 1:
The patent implements feedback mechanisms through automated data reconciliation that continuously monitor data consistency across multiple sources. When inconsistencies are detected, the system automatically initiates reconciliation processes to resolve conflicts and maintain data consistency. This feedback loop ensures that data completeness is maintained while automatically correcting inconsistencies, reducing the manual reconciliation effort required.
3Adaptability or versatility
If manual workarounds are used to access fragmented data, then flexibility in data access is improved, but user experience consistency and operational efficiency worsen
Solution Approach 1:
The data reconciliation service acts as an intermediary that standardizes data access across the system. By providing a unified interface for accessing reconciled data, the service eliminates the need for users to manually navigate through fragmented data sources and workarounds. This maintains the flexibility of accessing data from multiple sources while presenting a consistent, simplified user experience through the reconciliation service's standardized access mechanisms.
Data Source
AI summary
An interactive distributive platform apparatus configured to be a single source of truth. The platform may include entity identifier data stored in a database. The data may be placed in a grid through an AI algorithm. The AI algorithm may place the data in the grid using one or more rules. The data may be extracted into datasets. The datasets may be placed in corresponding selected nodes. Placement of the datasets may occur using smart contracts. The nodes may be part of a holochain. The datasets and rules may be validated in an interactive distributive platform. The interactive distributive platform may be the single source of truth. The interactive distributive platform may direct any request that enters the system to the correct node.