Predictive Transactional Document Generation for Reduced Computational Load
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems face challenges in efficiently processing and executing transactions due to increased computational resource strain from rapid document production and communication, leading to manual processes and inefficient communication between parties.
Innovation Solution
Implementing a transactional document service server with a predictive model that processes documents, generates transactional documents like invoices, and facilitates automated and adaptive transaction execution through multiple feedback loops, reducing computational resources and communication requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used for document processing and transaction execution, then computational resource strain is reduced, but processing efficiency and transaction completion speed deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-processing documents with the predictive model to extract transactional information and generate draft transactional documents before actual transactions occur. This advance preparation reduces the computational burden during actual transaction execution, as the heavy lifting of document analysis and information extraction has already been performed.
Solution Approach 2:
The system implements feedback loops where the predictive model continuously learns from transaction outcomes and document processing results. This feedback mechanism improves the model's accuracy over time, reducing the number of iterations and computational resources needed for each subsequent document processing task while maintaining high transaction execution efficiency.
2Reliability
If multiple communications are exchanged between parties for transaction completion, then transaction accuracy is improved, but communication time and processing duration increase
Solution Approach 1:
The predictive model performs preliminary analysis of documents and context data to pre-determine transactional information, generating draft transactional documents that are already highly accurate. This preliminary action reduces the need for multiple back-and-forth communications between parties, as the initial document is closer to final approval, thereby reducing communication time while maintaining transaction accuracy.
Solution Approach 2:
The system enables self-service by automatically generating transactional documents and updating context data without requiring extensive manual verification and communication between parties. The predictive model autonomously processes documents and makes informed decisions, reducing the need for human intervention and multiple communication cycles while maintaining high transaction accuracy.
3Manufacturing precision
If comprehensive document processing and review are performed, then transactional document accuracy is improved, but computational processing time increases
Solution Approach 1:
The system performs preliminary processing of documents using the predictive model to extract key information and generate draft transactional documents. This preliminary action captures the essential information needed for accurate transactions without requiring exhaustive manual review of every document detail, thereby maintaining document accuracy while reducing overall processing time.
Solution Approach 2:
The patent replaces manual mechanical review processes with an automated predictive model that uses machine learning to process documents and generate transactional information. This substitution maintains high document accuracy through intelligent analysis while significantly reducing processing time compared to manual review methods.
Data Source
AI summary
A computer-implemented method includes a transactional document service server receiving data representing a document and generating, by a predictive model, a transactional document. The predictive model processes the data representing the document along with context data. The transactional document service server receives data representative of a review of the transactional document in which the data representative of a review includes a modified transactional document. In response to receiving the data representative of a review and the modified transactional document, the server updates the context data and initiates a communication of the modified transactional document from a first party to a second party.