Multimillion dollar decisions are never without risk but basing them off of problematic data is simply reckless. Using “good enough” intellectual property data to make decisions can be dangerous. Often, time is wasted correcting raw data from global patent offices or your critical decisions are made on data that is rife with spelling errors, doesn’t reflect patent reassignments, and doesn’t account for M&A activities.
With Innography, you start with a robust IP dataset that our clients call the 'closest to reality,' so you can spend your time on valuable analyses and making decisions for your business rather than fixing incorrect data.
Innography leverages machine learning to take a big data approach to global IP data, drastically improving data quality. Our proprietary processes and algorithms turn data from nearly 200 sources into usable, verified, update-to-date information.
Innography was built on a thoroughly modern architecture and with the latest technologies and improved each year. Innography’s data-cleansing capabilities are unique in the industry.
The Innography database utilises crowdsourcing to find exceptions and generate new rules that only a person can decipher, in a “virtuous cycle” that increases accuracy as more people use it.
All this is overseen by our team of data scientists, who are charged with creating the cleanest data sets possible, while constantly adding new data sources and updating their technology approach.
Artificial Intelligence and machine learning in the future of IP
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