Artificial Intelligence has transformed intellectual property (IP) by reducing human effort and enabling patent experts to refine their methods for discovering, analyzing, and leveraging intellectual property. It’s no surprise that a Google search for AI-based non-patent tools or databases will yield hundreds, if not thousands, of platforms available at your disposal.
To make your search for the best AI-based non-patent tools easier, this article skips the redundant details and dives straight into the heart of the matter.
We delve into the impact of AI on NPL searches and highlight 13 of the most promising AI-based tools that are reshaping the way patent experts approach prior-art and freedom-to-operate (FTO) searches. This list will be updated as more AI tools emerge and the technology continues to evolve.
Additionally, for those looking to optimize their search workflow, be sure to check out our article on the Top 13 AI-based Patent Search Databases in 2025 by GreyB.
The Traditional NPL Search Dilemma
Prior-art searching has always been a cumbersome and tedious task. Researchers have relied on platforms like Google Scholar and IEEE Xplore, hoping the right combination of keywords would yield relevant results. However, these platforms have limitations, particularly in terms of their semantic search capabilities. Enter AI, the technology that replaces keyword-based searching with advanced semantic search, vastly improving accuracy and saving valuable time.
While these AI-powered tools are often used in academic settings, they have proven to be incredibly effective in the IP world, enabling researchers to uncover novelty-destroying prior art that traditional methods would miss. Let’s take a closer look at some of the leading AI-based NPL tools that are revolutionizing the process.
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Undermind.ai
Undermind.ai is an AI platform specifically designed for Non-Patent Literature (NPL) searching by moving beyond traditional keyword limitations. What immediately sets it apart is its conversational approach to building the perfect prompt.
Instead of requiring a user to master prompt engineering, the tool engages in a chat-based dialogue. It asks clarifying follow-up questions to build a comprehensive understanding of the technology or concept being investigated. This interactive process yields an exceptionally polished, AI-generated prompt that accurately captures the core idea of the search.
The true power of this conceptual approach is its ability to find highly relevant papers that other methods might miss. Once the search is complete, Undermind.ai generates an exhaustive research report, complete with organized references and an initial AI analysis, accelerating the shortlisting process compared to manually filtering results from platforms like Google Scholar.
Consensus
Consensus works as an AI-based academic search engine specifically created to provide direct answers to complex questions by extracting key findings from scientific literature.
It is particularly effective in dense technical and biomedical fields where the inventive concept lies in a newly discovered relationship between known elements. This makes it an incredibly efficient tool for the initial stages of a prior art search, allowing researchers to quickly validate whether a specific hypothesis has already been explored.
Consensus is a Question-Driven Evidence Engine that accelerates the “is this known?” phase of IP searches. Unlike traditional tools that search by keywords, it directly answers research questions by extracting insights from peer-reviewed papers, providing a rapid, evidence-based assessment of an invention’s novelty.
Elicit
Elicit functions as an AI research assistant that helps organize and analyze findings from multiple academic papers. Rather than working through documents individually, it synthesizes results into structured tables that make comparison easier. For instance, a researcher could ask a question such as “What were the known limitations of [technology X] before [priority date]?” and quickly generate evidence that might support or challenge an obviousness argument.
One of its key advantages is the ability to automatically extract and align specific data points across different sources. This reduces the manual effort typically required for feature charting and allows researchers to identify patterns, limitations, or overlaps more efficiently. By turning a time-consuming task into a single, automated query, Elicit enables a more streamlined approach to building cases during prior-art searches.
Scite.ai
Scite.ai focuses on the context in which a paper is cited, offering insight into the broader scientific conversation surrounding a reference. Its Smart Citations feature classifies citations as supporting, contrasting, or mentioning, helping researchers understand how a work has been received and evaluated by the academic community.
For patent professionals, this context can be particularly useful during invalidity searches. A reference that is frequently marked as contrasting may signal weaker reliability, while one with a high number of supporting citations can serve as stronger evidence. By highlighting these patterns, Scite.ai adds a layer of credibility assessment that goes beyond simple citation counts, making it easier to gauge the strength of a paper as prior art.
Bohrium
Bohrium, developed by DP Technology, is an AI-powered research platform designed to support large-scale scientific exploration. It provides access to more than 160 million research papers, 140,000 journals, 160 million patents, and 20 million scholar profiles across 26 academic fields. The platform is supported by proprietary scientific language models, such as DeepThink R1, and integrates with GPT-4o to enhance usability.
Bohrium combines multiple functions within a single environment, including AI-powered summaries, interactive chat-based interfaces, and domain-specific search options. By unifying access to diverse sources and enabling advanced analysis, it helps researchers navigate complex literature more effectively than traditional tools.
Paperpal
Paperpal is primarily known as a writing assistant, but it also supports research in its early stages. Its Research and Cite feature allows users to conduct semantic searches for concepts before a given cut-off date.
This makes it helpful in refining search queries or validating initial ideas before conducting a full prior-art or patent search.
R Discovery
R Discovery serves as a personalized research feed for ongoing monitoring of non-patent literature. Once trained on key papers in a specific field, the platform continuously surfaces new and relevant publications as they appear.
This functionality is particularly helpful for long-term projects or technology areas where new work is published frequently, ensuring that important references are not overlooked in one-time searches.
Science Space
Scispace provides an AI-powered “Copilot” for in-depth examination of specific references. Researchers can upload a document and query it directly, for example, asking about methodologies, data ranges, or experimental details. This allows verification of disclosures relevant to claim elements without reading the entire paper, significantly reducing review time.
Beyond this capability, Scispace includes a range of additional features such as chat with PDF, literature review tools, paraphrasing, citation generation, and even data extraction. These functions make it a versatile platform for analyzing, interpreting, and presenting non-patent literature in the context of prior-art searches and academic research.
Conclusion
The integration of Artificial Intelligence has unquestionably transformed the approach to prior art searches. AI-based non-patent tools, as discussed here, have become indispensable tools for patent professionals and researchers. The ability of AI to provide insights into hidden patterns, enhance search precision, and expedite patent assessments is evident.
Considering that these AI-driven tools will only continue to improve, it is essential to adapt and fully utilize their capabilities. However, AI patent tools alone amount to nothing. It is the combination of AI and manual expertise that gives top-tier results. Together, they not only streamline patent search processes but also ensure that no stone is left unturned.
Experience the potential of this powerful combination in your next patent invalidity and freedom-to-operate (FTO) searches.
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