AI-supported field extraction from documents has been available to the market for several years. Early implementations of AI for document processing began to emerge in the mid-2010s. Notable advancements and broader market availability started around 2017-2018, with the development and release of various AI-powered OCR (Optical Character Recognition) and document understanding services by major tech companies like Google, Microsoft, and Amazon.
Today, fully automated extraction of document-specific contents and feeding them into your application or database is a common use case in many industries.
While implementing your own logic to handle one or two simple, consistent, and invariable forms might not be a challenge, adapting to a multitude of different and ever-changing templates and sources quickly poses a complex and costly problem.
What if
This topic provides insights on the features and possibilities of integrating Azure Document intelligence into Omnis so that your application can extract the data content out of anything and place it into data fields.
Plattform overview and setup
Demo of Omnis integration with Document intelligence
Preparing for the session:
Appropriate materials and code will be provided as part of the sessions. However, to get the most out of the session, setting up a few thins in avance would help:
Sample documents will be provided, but you’re welcome to bring your own documents and train your models based on your specific requirements or ideas.