Technology: Docker Compose in GitLab CI Pipelines
At Rossum, we use GitLab for development, including running CI (Continuous Integration) pipelines for our code testing. In this post, we delve into some tips and tricks to get this
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Update on Rossum's line item extraction from invoices
At Rossum, we have been hard at work researching line item extraction from invoices. It is a daunting task, but we are not afraid. We know you have been waiting
Automating data extraction from invoices using Rossum API and UiPath
In this tutorial, you learned how to fully automate the process of data extraction from invoices using UiPath Studio and Rossum API. Rossum’s cognitive data capture technology is unique because
Extracting invoices using AI in a few lines of code
This blog post has been updated as of June 2019. Our AI researcher, Bohumir Zamecnik, has long been exploring new ways to extract data from invoices. What people originally were
Does Adding One Neuron Help Real World Networks?
Our researcher, Tonda Hoskovec, has long been thinking about the behavior of neural network training in the case of non-convex tasks with many local minima. This makes training difficult or
How to automatically read data from invoices using Rossum API: an example with Google Drive
Our research programmer, Roman Sushkov, recently posted a neat example of how to use Rossum’s Data Extraction API in practice. We think it is a great introduction to practical usage of
The Future of Data Capture Systems (2/2): The Rossum Approach
This is the second part of our special founders blog post on data capture technology and how Rossum represents a radically different approach to the whole problem of information extraction
Building Our Own Version of AlphaGo Zero
At Rossum, we are building artificial intelligence for understanding of documents. Our main line of attack lies in supervised machine learning, the most efficient approach to make neural networks achieve
Towards Efficient Multi-GPU Training in Keras with TensorFlow
At Rossum, we are training large neural network models daily on powerful GPU servers and making this process quick and efficient is becoming a priority for us. We expected to
