NLPatent
Legal Solutions · Canada · 11-50 Employees
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Overview
Headquarters
127 Priscilla Ave, Toronto, Ontario, M6S...Website
www.nlpatent.comRevenue
<$5 MillionIndustry
ZI Rank: 1
Signal Type
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ZI Rank
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About NLPatent
The semantic search techniques utilized in NLPatent take advantage of the latest Natural Language Processing and Machine Learning techniques to completely revolutionize an outdated and inefficient process. The company's ML models were purposefully built to understand patent language, which is notoriously obtuse, technology specific, and evolves overtime. In the information age, where billions of documents are at the company's finger tips, the process weve designed empowers IP and R&D professionals to find better results, rather than generating a laundry list of irrelevant references. NLPatent is sophisticated enough for a patent attorney to quash a patent in an IPR, yet simple enough for an R&D professional to quickly assess novelty of a new idea. It has been described as a total game changer by the company's clients, taking a process that has been regarded as a barrier to innovation into the 21st century, and were just getting started.Explore more
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NLPatent is experiencing very low activity levels compared to other companies in the Software sector.
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NLPatent is drawing exceptional interest within the Software industry, suggesting notable developments or strong market momentum, learn more about NLPatent.
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2024
Angel/Seed
$1.5M
NLPatent Tech Stack
A closer look at the technologies used by NLPatent
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Hiring Plans
NLPatent has more open roles in Engineering & Technical than it has had at any time in the past 12 months. Technologies mentioned include: Django, Git, Docker, Amazon AWS, Elasticsearch, and Python. Areas of expertise include: TensorFlow, Search Algorithms, Database Search Engine, Data Pipelines, Natural Language Processing (NLP), Machine Learning Model Training, and Python (Programming Language).
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The semantic search techniques utilized in NLPatent take advantage of the latest Natural Language Processing and Machine Learning techniques to completely revolutionize an outdated and inefficient process. The company's ML models were purposefully built to understand patent language, which is notoriously obtuse, technology specific, and evolves ove... Read More
