The AI Secret Weapon Every Patent Professional Will Be Using in 2025
Share:
The past few years have marked major milestones in the use of AI for day-to-day IP tasks, taking it from concept to reality. Since the launch of PatSeer’s AI search in mid-2023, we are currently averaging two out of every ten searches being an AI search on our systems and the ratio is increasing each month. While Boolean searches remain the dominant form of searching, AI’s ability to understand contextual relationships and hidden meanings is speeding up intellectual property search tasks that previously took days to complete.
Unlike Boolean searches, AI search engines can continuously improve in accuracy with better fine-tuning, giving AI a significant advantage for increased usage. For instance, we recently launched our AI search v2 engine that was a result of extensive downstream training and fine-tuning across all technology domains, and it resulted in a 33% average improvement in search quality compared to our v1 engine.
Rise of Combinational AI
Do you use AI for one type of search and Boolean for another, or as a fallback?
Chances are that you will be hearing more about Combinational AI in the future, as expert search platforms integrate AI deeply within their systems. At PatSeer, we have always believed deeply in this and so it has been core to our platform design.
Combinational AI is more than just having AI search and Expert Search capabilities in a single platform.
Here’s how it can be explained:
Combining Expert and AI searches on a single platform offers immediate advantages such as cost savings, time savings in merging results or integrating alerts, and a reduction in overheads (data gaps, sharing, export formats) that can lead to errors.
A true combinational AI system takes this a step further, allowing you to leverage AI tools with your Boolean results or integrate Boolean and AI within your search strategies. This opens new ways of searching and analysis enhancing both patent analytics and design patent search. For instance, with Combinational AI, your search scripts can look like:
Going Beyond Search
For corporate IP teams, searching is just one part of the overall IP intelligence operations with FTO reviews, Competitive Intelligence, Innovation Scouting, Monitoring and Landscaping being some of the other important projects that are done from time to time. An integrated solution that addresses all these requirements helps avoid the typical data integration, cross-collaboration, and duplication challenges caused by disconnected systems.
The use of generative AI in summarizing long, complex documents or comparing claims between documents has seen rapid adoption, making it easier for R&D and non-IP professionals to work with patents. Comparing patent claims is a painstaking process, especially when subtle differences in wording or legal language can have major implications for patent validity or FTO reviews. AI is simplifying this process by automatically highlighting and comparing claim differences.
For Competitive Intelligence, Landscaping and Monitoring, most organizations are used to maintain categorized patent data sets. This categorization process lets IP professionals easily manage competitor portfolios, track trends, and retrieve relevant patents with minimal effort, allowing for more proactive IP risk management strategies that better support long-term business goals. Platforms such as PatSeer allow users to leverage their already trained tagged datasets to build custom trained AI Classifiers which can help do away with the tedious manual categorization, improving the efficiency of your design patents and patent databases.
AI for image similarity searching
With design registrations and litigations rising, scrutiny of novelty and originality has increased, necessitating advanced better systems to conduct Design FTO and patent searches. An image speaks a thousand words and when it comes to Design patents, an image is the only thing speaking to you. Till date, users have relied solely on Classification only searches that leave them no option but to scan thousands of images for each search. Recognizing this challenge, at PatSeer we have recently launched an AI-driven worldwide design search solution, built over a fine-tuned computer vision model. By understanding finer nuances such as line-drawings and photos the new search engine sets a new bar for image similarity matching and redefines how design images are searched.
The platform leverages the same Combinational AI benefits mentioned earlier to make it even more powerful, you have access to enriched value-added content for each design record, which helps you create more powerful search queries improving your intellectual property software capabilities.
Agentic AI and AI assistants
If 2023 was about LLMs, 2024 has been about RAG and 2025 will be about agentic-AI. AI Agents can solve complex and multi-step problems by breaking them into steps and employing sophisticated reasoning and decision-making capabilities at each step.
Our aim with AI assistants is to answer beyond level one cognitive capabilities such as summarizing a record and comparing claims of records which are already available upon a single click of a button.
Need of the hour: Benchmarking AI quality
Many companies struggle with benchmarking AI search quality. This is a common challenge faced when teams are given a task to select a database from the available AI based patent search systems.
Since no standard metrics exist, users are unable to provide quantifiable answers to questions such as how does the AI result quality compare with a professionally done search or with another set of results. Purely predictive metrics like Precision and Recall are not well-suited for the task since they do not give any consideration to the order of results.
PatSeer is an AI-driven IP research platform trusted by 8,000+ professionals worldwide. Covering worldwide patents and designs, and with solutions designed for IP teams and R&D, it offers an integrated end-to-end IP research solution for innovation-driven organizations of all sizes.
