Cognitive data capture uses artificial intelligence (AI) to mimic the way the human mind reads structured documents. This approach has two key features: the AI learns to recognize information through exposure to examples rather than manual configuration by experts, and it can recognize a lot of information in documents with layouts it hasn’t seen before.
Contrary to manual data entry or traditional OCR, cognitive data capture does not require extra manpower. It also saves you the hassle, time, and cost of setting up endless rules and templates (you can read detailed comparisons of effort in our TCO analysis series).
Rossum’s cognitive data capture AI uses deep neural networks to recognize patterns in documents like a human mind would. This enables the platform to understand the underlying general structure of business documents like invoices. Rossum’s unique neural network architecture allows it to comprehend a vast range of layouts; it also ensures highly accurate data extraction.
Refer to our founders’ blog series on cognitive data capture for an in-depth look at the technical difference between legacy OCR solutions and cognitive data capture, and how Rossum’s technology works.