AI-Assisted Document Review Annotation System
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Solution Overview
Problem
Current methods for document review meetings face challenges in accurately capturing and consolidating feedback from participants, as they often rely on manual note-taking and handwritten comments, which can lead to inconsistencies and inefficiencies in incorporating suggestions into the original document.
Innovation Solution
An apparatus comprising processors and memories that automatically identify and generate annotations for content suggestions from various sources, including physical and electronic documents, and media content, associating these suggestions with their corresponding document portions and displaying them electronically for easy review and editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual note-taking and handwritten comments are used to capture feedback during document review meetings, then participants can provide suggestions, but the accuracy and consistency of capturing and consolidating feedback deteriorates
Solution Approach 1:
The patent replaces manual mechanical note-taking processes with an automated electronic system using optical character recognition (OCR) and image processing. The system captures images of handwritten comments and physically marked-up documents, then automatically converts them into structured digital annotations linked to specific document portions, eliminating manual transcription while preserving the ease of handwritten input.
Solution Approach 2:
The patent creates digital copies of physical documents and handwritten comments through imaging technology. The system captures images of marked-up physical documents and handwritten notes, then processes these images to generate electronic annotations that are linked to the corresponding digital document portions, preserving the original feedback while enabling automated processing.
2Quantity of substance
If manual consolidation of comments from multiple participants is performed, then all feedback can be collected, but the time and effort required to ensure accurate capture and incorporation of all comments increases
Solution Approach 1:
The patent implements a self-service system where the automated processing system independently performs the consolidation task. The system automatically processes images of marked-up documents, identifies comments and suggestions, links them to corresponding document portions, and generates consolidated annotations without requiring manual intervention, thereby collecting comprehensive feedback while eliminating the time loss associated with manual consolidation.
Solution Approach 2:
The patent introduces an intermediary automated processing layer between the collection of handwritten comments and their consolidation into the final document. This intermediary system uses OCR and image processing to bridge the gap between physical feedback and digital documentation, automatically extracting and organizing comments from multiple participants into a unified structured format.
3Adaptability or versatility
If handwritten comments and physical mark-ups are used, then participants can annotate documents, but the efficiency of incorporating suggestions into the original document deteriorates
Solution Approach 1:
The patent replaces the mechanical process of manually transcribing and incorporating handwritten comments with an automated electronic system. The system uses optical character recognition and image processing to convert physical mark-ups and handwritten notes into digital annotations that are automatically linked to the electronic document, maintaining the flexibility of handwritten input while dramatically improving the efficiency of incorporating suggestions.
4Productivity
If automated systems are introduced to capture and process feedback, then the efficiency and accuracy of feedback incorporation improves, but the complexity of the system increases
Solution Approach 1:
The patent implements a multi-functional automated processing system that performs multiple tasks within a single integrated framework. The system simultaneously handles image capture, optical character recognition, comment extraction, document portion identification, annotation generation, and consolidation, thereby improving productivity while managing complexity through functional integration rather than separate specialized components.
Data Source
AI summary
Artificial intelligence is introduced into document review to identify content suggestions from input to generate suggested annotations for the reviewed document. An approach is provided for receiving an electronic document that contains original content from an original electronic document for review and electronic mark-ups provided by a first user. One or more electronic mark-ups that represent content suggestions proposed by the first user are identified from the electronic document. For each electronic mark-up of the one or more electronic mark-ups identified a document portion of the original content that corresponds to the electronic mark-up is identified, and an annotation is generated for the electronic mark-up comprising the electronic mark-up and a first user ID for the first user and associating the annotation to the document portion identified. The original content with one or more annotations generated from the one or more electronic mark-ups is displayed, in electronic form, within a display window.