Since its inception, LexisNexis Intellectual Property Solutions has been at the forefront of providing cutting-edge analytics and insights to global IP professionals and business leaders. Long before the recent buzz surrounding AI, sparked by the launch of ChatGPT and generative AI technologies, we have been steadily integrating AI-driven IP analytics into our solutions. Over the years, we have continually evolved our product offerings to meet the changing needs of our customers, leveraging advanced technologies such as machine learning and artificial intelligence (AI).
This blog outlines the development of our AI-driven IP analytics products and features over the past decade and highlights how these innovations enable enhanced customer experiences.
Figure 1: Evolution of AI-driven IP solutions at LexisNexis Intellectual Property Solutions
Our journey into AI-driven IP analytics and machine learning began in 2013, a time when AI was far from the mainstream conversation. With the introduction of Cipher Patent Clustering, we pioneered the use of unsupervised machine learning to group patents based on their similarities. By leveraging this technology, our customers could easily identify clusters of related patents, streamlining the process of patent portfolio management and competitive analysis.
Building on the foundation laid by Cipher Clustering, In 2015, we developed Cipher Classifiers. This tool employed supervised machine learning to classify patents into predefined categories. Integrating a human feedback loop into the process significantly improved the accuracy and efficiency of patent classification, enabling our customers to organize better, analyze and gain insights from their patent data.
Recognizing the global nature of innovation, in 2016, we launched TotalPatent One Machine Translations. By harnessing AI, we broke down language barriers, providing our customers from across the globe with access to a broader, reliable range of patent information by automatically translating patent documents into multiple languages.
In 2020, we introduced PatentSight+ Technology Clusters, a solution that utilized natural language processing (NLP) to group patents into technology clusters. This tool gives our customers deeper insights into technological trends and innovation landscapes, aiding in strategic decision-making and competitive intelligence.
2021 was a milestone year with the launch of PatentSight Similarity Search, which employed natural language processing(NPL) to identify similar patents based on textual content. This enhanced our customers’ ability to find relevant patents and conduct prior art searches from a different perspective.
Later, in 2021, we enhanced our machine translation capabilities through a strategic alliance with Microsoft. By leveraging their large language models, we improved the accuracy and quality of our patent translations, ensuring that our customers receive reliable and precise information across different languages.
In 2022, we launched two groundbreaking features. TotalPatent One Guided Simple Search used NLP and machine learning to provide an intuitive and user-friendly search experience, making it easier for customers to find relevant patents. Additionally, the IPlytics Standard Essentiality Scoring utilized machine learning to assess the essentiality of patents to industry standards, offering valuable insights for standard-setting organizations and patent holders.
Our most recent advancement in AI-driven IP analytics came in 2023 with the introduction of TechDiscovery in Classification. This feature leverages generative AI and supervised machine learning to revolutionize the patent search process. It enables customers to build entire patent landscapes from a simple one-word search prompt, drastically speeding up the process.
Our integration of AI into our products has always been deliberate and focused on improving the accuracy and efficiency of our IP solutions. Tools like Cipher Classifiers and the Universal Technology Taxonomy have automated the classification process, freeing our customers to focus on higher-level strategic tasks rather than manual data processing.
AI-driven solutions such as the PatentSight+ Technology Clusters and Cipher Universal Technology Taxonomy provide enhanced insights into technological trends and complex patent landscapes. These tools help IP professionals and business leaders make informed decisions regarding patent portfolio management, competitive analysis, and strategic planning. By understanding the broader context of their patents, our customers can better align their innovation strategies with their business goals.
Our unwavering commitment to security and privacy is at the core of our product development. Our Privacy by Design philosophy ensures that user activity and model interactions are limited to the individual and that our generative AI models are private, not shared with third parties.
Built on commercial-grade cloud infrastructure, our AI tools manage performance and security with utmost rigor, leveraging secure model deployment options from providers like Microsoft Azure and AWS. The launch of TechDiscovery will be the first instance in the IP industry to combine AI and human intelligence, delivering high-quality results based on supervised machine learning capabilities.
Our AI development is also guided by the RELX Responsible AI Principles, which are defined by our parent company, RELX. These principles emphasize transparency in model performance and bias-free implementation.
As we look to the future, we remain committed to driving innovation and delivering advanced solutions that empower IP professionals and business leaders worldwide.
Want to learn more about our AI offerings? Visit our AI hub here.
Members of the PatentSight+ AI-Insider program will lead the advancement of artificial intelligence in intellectual property and help revolutionize the way high-value strategic insights can be gained from AI-powered IP search and analytics.
