Can we strengthen the prior art for a patent examination? Video case study on Nike patent


February 9 2018

Patent examiners are well know for their diligence when searching for prior art. Nonetheless, there is always scope to improve any process, particularly when new tools that apply innovative thinking become available. And Ambercite Ai is such a tool - by applying AI processes to a database of over 150 million patent citations and 50 million patent families, it can quickly suggest new prior art.

To provide an example of this, we have created a video case study. The patent application in question is  WO2016196217, filed by Nike for Enhancing exercise through augmented reality. This application:

 describes monitoring a user's performance and generating a virtual representation of that user's performance to be displayed during a future exercise routine to motivate the user to improve performance during their next workout.

Or in other words, using an 'avatar' to motivate performance. 

Nike patent picture

The PCT search report showed 5 documents.

In the video case study, we show how a combination of 

  • Ambercite's ability to find similar patents using nothing more than a patent number
  • A simple key word highlight and filter

Can quickly find similar and relevant prior art - even that which has not been cited against this patent application. 


The patents found include:

US8033996, Computer interfaces including physiologically guided avatars 

US8033996 image.gif

And US9199122, filed for a Personalized avatar responsive to user physical state and context

US9099122 image.gif


Why is Ambercite different to other patent databases and patent search tools?

Rather than making risky assumptions about relevant keywords or classcodes, Ambercite instead relies on the collective wisdom of the patent examiners and applicants who searched and filed patents for similar inventions. This is expressed through our database of 156 million patent citations and 57 million patent families. Ambercite has developed special algorithms that can mine this billions of hours of collective endeavor, and instantly predict similar patents.

Any search done in Ambercite will be completely confidential - Ambercite does not record any search query or the results obtained.

Please contact us for further information.