Using true AI to create real value

by Agata, head of AI

The number of documents being published by the political institutions is overwhelming, even taking into account single countries. Harnessing such big volumes of data coming instantly from multiple sources requires not only creation of a central point of information, but also finding ways of effective processing of these data without the (impossible to fulfill) necessity of manually reading all of them. That’s where the great potential of Artificial Intelligence (AI) comes into play, finding hidden patterns in the data, that could be hard or even impossible to find with the human eye. 
 
At Policy-Insider.AI (PI.AI) we believe, that time is one of the most valuable assets: PIAI allows you to get the needed information in no time so that you can make better use of your time and concentrate on the creative work.
But more importantly, we want to prove that the cooperation between human and machine can bring us to a totally new level of productivity, allowing us to get into crucial insights of such complicated areas like politics. 

Our team of Artificial Intelligence engineers works constantly on the development and improvement of machine learning algorithms:  creating the heart of policy insider, thy enable you to work smarter and connect dots you had never seen before.

Policy-Insider is powered by AI algorithms in many areas, involving i.e.:

  • dedicated translator – newest neural network architectures trained to specifically deal with political language allow you to overcome the language barriers and work with documents created in languages you don’ master,
  • classification into policy areas – automatic detection of main focus areas of the documents trained based on opinions of policy experts give you the context of discussions about your topic of interest 
  • search recommendations – recommendations of connected topics created based on content of hundreds of thousands of political documents, which may expand your field of analysis,
  • similar and referenced documents – automatically matched documents which were referenced by or referencing particular document and recommendations of similar documents based on their content.

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