Google Patents Integrations

Google Scholar is a freely accessible search engine that specializes in indexing and providing access to scholarly literature across various disciplines and formats. It allows users to search for articles, theses, conference papers, preprints, technical reports, books, and other academic publications from a wide range of sources, including universities, research institutions, academic publishers, and professional societies. Google Scholar aims to help researchers, students, and professionals find relevant academic resources for their studies or projects. Users can search by keywords, author names, or publication titles, and the results often include direct links to the full text or, in some cases, abstracts and citations. The search engine also provides tools to help users track citations, find related articles, and export citations in various formats.

When you rely solely on a conventional patent search database, you depend heavily on keywords and semantic association. This search process can be notoriously inexact, laborious, and time-consuming. By contrast, Ambercite Ai uses deep-learning and network algorithms which find the most similar patents to one or more starting patents. Results are ranked by similarity, and searches are extremely quick and easy. Combine your unique expertise with the deep-learning ability in Ambercite Ai to give you an unfair advantage. We identify what are likely to be the most similar and most important patents close to the patents that you are interested in, using advanced methods based on our AI algorithms and our database of over 106 million patents and 175 million patent citations. This saves you time and money otherwise lost on reading low-value patent documents. Abstract, representative image, and smart review features can then allow you to hone into the patents that you are looking for.