Dynamic Notary Session Matching for Document-Specific Routing
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Solution Overview
Problem
Current systems struggle to efficiently match users with qualified and available notaries for remote online notarization, particularly in determining document-specific and user-specific notary requirements, leading to burdensome processes and increased waiting times.
Innovation Solution
A system that utilizes machine learning models to classify documents, determine notary requirements, and dynamically connect users with qualified notaries, optimizing the matching process by considering document-level and user-level criteria, and adjusting priorities based on real-time availability and performance metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional in-person notary services are used, then users can receive notarization services, but the process becomes burdensome and time-consuming due to the need to manually search for qualified notaries and review regulations
Solution Approach 1:
The system enables automated self-service by allowing users to upload documents and receive automatic matching with qualified notaries based on document analysis, eliminating the need for manual searching and scheduling
Solution Approach 2:
The patent replaces manual mechanical processes (physical document review, manual notary searching) with automated computer-based document classification algorithms and dynamic routing systems that automatically match users with qualified notaries
2Adaptability or versatility
If remote online notarization is implemented, then accessibility is improved, but systems struggle to efficiently determine document-specific notary requirements and match users with qualified notaries
Solution Approach 1:
The system dynamically changes matching parameters by analyzing document-specific requirements extracted from uploaded documents and adjusting notary qualification criteria accordingly, enabling efficient remote matching based on actual document needs rather than static rules
Solution Approach 2:
The system performs preliminary document classification and requirement determination before the notary matching process, pre-identifying qualified notaries based on extracted document characteristics to accelerate the matching efficiency
3Measurement precision
If manual document review processes are used, then notary requirements can be determined, but the process is slow and increases waiting times
Solution Approach 1:
The patent replaces manual document review with automated document classification algorithms that use machine learning to extract requirements and determine notary qualifications, maintaining precision while dramatically reducing processing time
Solution Approach 2:
The system implements continuous automated document analysis and real-time notary availability checking, eliminating idle time between document review and notary matching that occurs in manual processes
Data Source
AI summary
Disclosed embodiments include a method for dynamically providing notary sessions. The method can include receiving a document and one or more user-level notary requirements from a user device. Data entries can be extracted from the document and the document can be associated with a template. Document-level notary requirements can be determined based on the template and document. A first subset of active notary devices can be identified, and a first join request can be transmitted to the first subset. A first notary session between a first notary device and first user device can be initiated if the join request is accepted within a predetermined time threshold. If the join request is not accepted within a predetermined time threshold, the method can include identifying a second subset of active notary devices, transmitting a second join request, and initiating a second notary session between the first user device and second notary device.