Doctoral project: AI-powered patent drafting

Project information

Doctoral student
Homam Mawaldi
Supervisor
Zenun Kastrati
Assistant supervisors
Arianit Kurti, Alexander Gustafsson
Participant organizations
Linnéuniversitetet, AWA
Financiers
AWA,The Knowledge Foundation (Industrial Research School for Data Intensive Applications (DIA))
Timetable
Oktober 2024 – Oktober 2029
Subject
Computer and information science (Department of Computer Science and Media Technology, Faculty of Technology)
Research group
Data Intensive Software Technologies and Applications (DISTA)
Linnaeus University Centre
Linnaeus University Centre for Data Intensive Sciences and Applications (DISA)
Graduate School
The industry graduate school Data Intensive Applications (DIA)

More about the project

In today's rapidly evolving technological landscape, drafting patent applications has become an increasingly complex task. Patent attorneys, who are responsible for translating innovative ideas into legally sound documents, face significant challenges in ensuring that patents are thorough, accurate, and legally robust. This is where AI-powered patent drafting can make a real difference.

This project seeks to revolutionize the patent drafting process by developing a suite of generative AI tools aimed at streamlining and enhancing the work of patent professionals. By leveraging large language models, the project provides an effective solution for automating key aspects of the drafting process, such as generating patent specifications, refining technical descriptions, and suggesting language that meets legal standards.

What sets this project apart is its emphasis on data security. Given that patent applications often involve highly sensitive intellectual property, protecting this information is of utmost importance. To address these concerns, the project integrates a secure, on-premise solution, ensuring that all data remains within the client's network, minimizing the risk of external breaches. This approach allows patent attorneys to take full advantage of AI while maintaining complete control over the confidentiality of their clients' innovations.

By incorporating AI into patent law practices, this project not only aims to save time and reduce human error, but also has the potential to drive innovation in the patent field. Offering a reliable and secure AI solution, it enables patent attorneys to focus more on the creative and strategic aspects of their work, ultimately reshaping the way intellectual property is protected and represented.

The doctoral project is performed within Data Intensive Software Technologies and Applications (DISTA), Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) and is part of The industry graduate school Data Intensive Applications (DIA).