Explore. Patent Language. Fast.
Applying artificial intelligence and deep learnig solutions in patent search and assessment
Speed-up your efforts finding technical phrases for your patent search or patent writing. With EQAlice specific technical terms can be found in seconds.
Find 100% authentic phrases. In our proprietary language database equal and near-by phrases are identified using our unique word embedding based on their technical meaning.
Make use of a language dataset tailored to the application with patents. Explore creative technical word combinations of million patent documentsin just a click.
We developed an own natural language process and trained our algorithm on more than 300 million patent phrases
Meet the Team
Abdullah studied Technology Engineering at Damascus University and Computer Science at the University of Bonn. Abdullah has a strong entrepreneurial footprint and supported several start-ups at the international UK Lebanon Tech Hub. Most recently worked as a research assistant at the Fraunhofer Institute for Intelligent Analysis and Information Systems.
Abdullah likes to explore the Siebengebirge with friends at the weekends, teaches programming to school classes and enjoys a traditional Sish Taouk.
Annalena studies mathematics at the University of Bonn, works part-time as a research assistant at the Fraunhofer Institute for Algorithms and Scientific Computing and supports the Corona School project on a voluntary basis. The development of new approaches to machine learning and the use of artificial intelligence in complex language makes her heart beat faster.
As a graduate in Asian Studiess she is a great friend of Indonesian culture and cuisine and has a sporting passion for badminton and judo.
Mark studied physics at the University of Bonn and is not only pursuing his PhD in the field of high-resolution silicon pixel detectors at CERN, but also working as a research consultant in a patent law firm in Cologne. His passion for data analysis is primarily devoted to the development and profiling of recommendation systems based on machine learning approaches on patent data.
In his spare time, Mark enjoys spending time with his family and friends, is engaged in the transition from science to start-ups and loves outdoor sports.
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Silvan studied international business at the University of Brighton and agricultural economics at the University of Bonn. In his doctoral thesis he developed techniques based on patent data to anticipate trends for corporate and technology developments.
As a management consultant, he also helps banks and insurance companies to align and manage their transformation strategies.
On weekends Silvan likes to spend his free time with his family and friends.
Or reach out to us
EQMania is part of the Accelerator Program of the DIGITAL HUB REGION BONN - a project funded by Digitale Wirtschaft NRW (#DWNRW). An initiative of the Ministry of Economic Affairs, Innovation, Digitalization and Energy of the State of North Rhine-Westphalia.