FMR had 11 patents in artificial intelligence during Q4 2023. FMR LLC filed patents in Q4 2023 for systems and methods involving data extraction from electronic documents using OCR and non-OCR based text extraction, personalized media clip generation for customer enrollment using AI, identifying diminished capacity in voice call participants through audio data analysis, and scoring investment data using machine learning-based model training. These patents focus on improving data processing, customer engagement, security protocols, and investment decision-making through innovative technologies. GlobalData’s report on FMR gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

FMR grant share with artificial intelligence as a theme is 63% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Systems and methods for automated end-to-end text extraction of electronic documents (Patent ID: US20230419711A1)

The patent filed by FMR LLC describes systems and methods for extracting data from electronic documents using a combination of optical character recognition (OCR) and non-OCR based text extraction. The server computing device initiates non-OCR based text extraction for each page of the document and calculates text coverage percentages to determine when to switch to OCR. If the text coverage percentage is below a certain threshold, OCR is initiated for the entire document or specific pages. The extracted text from both methods is then combined. The system also includes features such as determining if a page contains non-searchable images, calculating the accuracy of non-OCR text extraction, removing watermarks, and correcting misspelled words.

The method and system outlined in the patent aim to efficiently extract data from electronic documents by utilizing a combination of OCR and non-OCR based text extraction. By dynamically switching between these methods based on text coverage percentages, the system ensures accurate extraction of text from documents. Additionally, features such as determining image coverage percentages, calculating extraction accuracy, and handling non-searchable images enhance the overall data extraction process. The system also includes steps to store the extracted data in a database and correct any errors in the extracted text. Overall, the patent describes a comprehensive approach to data extraction from electronic documents using a combination of OCR and non-OCR methods.

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