This inventor holds 2 USPTO granted patents and 6 published patent applications. Top assignee: Relativity Oda LLC. Active years: 2025-2026.
Company Filing History:
Years Active: 2025-2026
Title: Somya Anand - Innovator in Legal Entity Identification
Introduction
Somya Anand is a notable inventor based in Vancouver, Canada. He has made significant contributions to the field of legal entity identification through his innovative patent. His work focuses on utilizing advanced machine learning techniques to enhance the identification of legal entities.
Latest Patents
Somya Anand holds a patent titled "System and method for automatic identification of legal entities." This patent describes systems, methods, and computer-readable media for identifying entities as legal entities. The techniques outlined in the patent include accessing a corpus of documents and applying a persona prediction machine learning algorithm to classify entities associated with the corpus. The algorithm consists of two layers: the first layer employs a signature block classifier that analyzes signature blocks of the entities, while the second layer utilizes an entity classifier that examines a variety of documents and network graphs related to the entities. The entity database is updated to reflect the output of the persona prediction machine learning algorithm based on the results from both classifiers.
Career Highlights
Somya Anand is currently associated with Relativity Oda LLC, where he continues to develop innovative solutions in the realm of legal technology. His expertise in machine learning and legal entity identification has positioned him as a valuable asset in his field.
Collaborations
Some of Somya's coworkers include Jasneet Singh Sabharwal and Ayushi Dalmia, who contribute to the collaborative environment at Relativity Oda LLC.
Conclusion
Somya Anand's work in the automatic identification of legal entities showcases his innovative spirit and dedication to advancing technology in the legal sector. His contributions are paving the way for more efficient and accurate identification processes.