DocuSign had 21 patents in artificial intelligence during Q4 2023. DocuSign Inc’s patents filed in Q4 2023 focus on a document management system that generates and validates online documents, customizing appearance and recommending modifications to increase validity. The system also includes an artificial intelligence-based document manager for predictive operations and training machine learning models to rank text suggestions in contracts. Additionally, the patents cover an online document system that tracks amendments to original documents and a distributed machine learning model trained using data from third parties via a blockchain system, allowing parties to contribute and remove their data while maintaining control. GlobalData’s report on DocuSign gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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DocuSign grant share with artificial intelligence as a theme is 47% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Customized agreement generation (Patent ID: US20230419013A1)
The patent filed by DocuSign Inc. describes a document management system that generates and validates online documents. The system allows for customization of online documents through various rendering parameters to customize the appearance of agreement content for the receiving entity. It also validates the rendering parameters to determine the likelihood of document validity, recommending custom templates or modifications to increase the likelihood of achieving the originating entity's objective. The system applies a machine-learned model to recommend target rendering parameters that would increase the likelihood of the receiving entity clicking an "Agree" button.
The method outlined in the patent involves receiving a document request from a client device, applying a machine-learned model to determine a target rendering parameter based on the receiving entity's features, modifying the document based on the likelihood of interaction, and providing the modified document to the client device. The system can select templates based on historical completion likelihoods, create templates with various rendering parameters, train the machine-learned model using historical data, and track user interactions to generate profiles. Additionally, the system can determine features of the receiving entity from profiles, store completion mappings, and ensure document security through encryption and authentication measures. Overall, the patent focuses on optimizing document rendering and completion through machine learning and customization features.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
