Get Documents Done.
When Alain Veuve and Jan-Hendrik Heuing were looking for a document extraction solution for one of their other startups back in 2017, they quickly realized that, contrary to the widespread belief in the market that anything is possible technologically, document extraction is in fact yet unsolved. There is a huge number of solutions, but they all have three things in common; they are cumbersome to set up, cost a lot, and produce mediocre results.
Having thus become aware of the problem, the young team at Parashift began researching machine learning-based technologies for the universal, global, autonomous document extraction on a greenfield site, so to speak. Three years later, a machine learning cluster is now in place, which systematically learns about all documents used in daily business transactions. And a product that helps customers in Germany, Switzerland, Austria, and the USA to read and understand documents faster and better.
Parashift has not yet reached its technological goal. The problem to be solved is large, costly, and complex. That’s why we are continuing to invest massively in the technology, so that we can come a small step closer to solving the document problem every day. This will continue until autonomous document extraction in companies of all sizes is as normal and incidental as email, for example.
We are convinced that autonomous data extraction will radically change the way companies shape their business. As we know it no other way, we still sometimes accept the vast amount of time and cost that is spent on manual document processing. But we believe that autonomous document extraction will trigger a paradigm change in business – far beyond the actual document processing. This is partly due to the fact that the document volume is continuously increasing and almost no process can do without documents.
Basic research in the field of Artificial Intelligence.
In-depth machine learning know-how.
The Parashift team is breaking new ground in the research of machine learning solutions. Our work on ML-based document extraction has led to various patents and proprietary technologies.
Parashift’s versatile machine learning platform.
We have developed a highly versatile machine learning platform that combines simple and efficient data and model management with human annotation of an ever growing pool of aggregated data.
Multidimensional machine learning clusters learn particularly well and quickly from qualified human interactions. We use this effect and scale our efficiency accordingly across all documents processed in the network.