INTERGATOR Patent Search

With INTERGATOR Patent Search, you combine the benefits of semantic and keyword-based search in a powerful query. Our AI-based technology understands the context and meaning of your search queries and delivers precise and relevant results, whether you’re researching individual terms, paragraphs, or entire documents. This allows for a more comprehensive and efficient patent search, as both contextual relationships and specific keywords are taken into account.

What is AI-Based Patent Search?

AI-based patent search utilizes artificial intelligence and machine learning to make the search for relevant patents more efficient and precise. Unlike traditional keyword-based methods, where specific terms are searched within texts, AI-based search understands the context and meaning of search queries. This allows for a semantic search of patent documents, significantly increasing the relevance of the results. By applying neural networks and complex algorithms, AI can identify similar patents, even if they use different terms.

INTERGATOR Patent Search Patent Viewer

Benefits of AI Patent Search over Traditional Methods

Efficiency, Accuracy, Time Savings

AI-based patent search offers numerous advantages over traditional search methods. Firstly, it is much more efficient as it not only relies on exact term occurrences but also recognizes contextual relevance, thereby providing more comprehensive results. Secondly, semantic search enhances the accuracy of search results by minimizing irrelevant hits and highlighting the most relevant patents. Thirdly, AI-based search saves considerable time. While traditional methods often require lengthy and complex queries, AI-based patent research can be conducted with just a few terms, paragraphs, or entire documents, thereby speeding up the research process and reducing workload.

Machine learning enhances patent research by continuously learning from large datasets and identifying patterns that are difficult for human search methods to access. By analyzing and understanding these patterns, AI can not only identify relevant patents more quickly but also establish semantic connections that traditional search approaches would overlook.

Semantic search improves patent research by understanding and interpreting the context and meaning of search queries. Instead of just searching for exact terms, semantic search recognizes the contextual relationships and thematic similarities between patents. This results in finding more relevant results, even when different terms are used, and significantly increases the accuracy of the research.

Keyword-based search combines the precision of traditional methods with the benefits of semantic search. While keyword-based search specifically looks for specific terms, the semantic component complements this by understanding the context and meaning of the terms. This combination allows for a more comprehensive and accurate patent search, identifying both exact matches and contextually relevant documents.