Technical Uncertainty Identification From Project Task Data
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Solution Overview
Problem
Current methods for identifying technical uncertainties and evaluating alternatives for research and development tax credits rely heavily on human memory, lacking effective tools to analyze task management and version control systems for documentation.
Innovation Solution
A system and method that utilizes processors and computer-executable instructions to electronically access and partition task data objects into objective groups, identify technical uncertainties, and assess evaluated alternatives by analyzing text strings and language models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods relying on human memory are used to identify technical uncertainties and evaluate alternatives, then subject matter experts can provide contextual understanding, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent introduces an intermediary system comprising a language model and documentation analysis module that acts as a mediator between raw documentation and tax credit qualification assessment. This intermediary automatically processes documentation, extracts technical uncertainties, and identifies evaluated alternatives, thereby reducing the time burden on subject matter experts while maintaining identification accuracy through automated text analysis
Solution Approach 2:
The patent replaces the manual mechanical process of reviewing documentation with an automated computational system. The language model and processing modules substitute human cognitive efforts, automatically analyzing task management system data, version control data, and documentation to identify technical uncertainties and alternatives, significantly reducing time consumption while preserving accuracy
2Productivity
If automated tools are introduced to analyze documentation, then time consumption is reduced, but the complexity of the system increases
Solution Approach 1:
The patent designs a multi-functional system where a single integrated platform performs multiple tasks: accessing task management data, analyzing version control information, processing documentation, identifying technical uncertainties, and evaluating alternatives. This universal system consolidates what would otherwise require multiple separate tools, managing complexity through functional integration while maintaining high processing efficiency
Solution Approach 2:
The system incorporates self-service capabilities where the language model automatically adjusts its analysis based on the specific documentation provided, and the system autonomously navigates different data sources without requiring complex external configuration. This self-service approach reduces operational complexity while sustaining productivity
Data Source
AI summary
Various embodiments are disclosed for identifying technical uncertainties for determining tax credit qualification, including electronically accessing project data comprising a plurality of task data objects, partitioning the plurality of task data objects into a plurality of objective groups, and identifying technical uncertainties associated with the task data objects of each objective group.