Summary
In this chapter, we discussed the current challenges in document processing and how IDP can help overcome those challenges. We introduced IDP by tracing the origins of AI, how it has evolved over the last few decades, and how AI became an integral part of our everyday lives.
We then reviewed industry trends and market segmentation and saw with examples how important it is to automate document processing. We also discussed IDP across industry use cases. We read an example of how patient data can be collected and enriched to better patient outcome prediction.
Finally, we reviewed the stages of the IDP pipeline such as data capture, data classification, data extraction, data enrichment, and data post-processing. This chapter gave readers an understanding of IDP and the various stages involved to automate the end-to-end pipeline.
In the next chapter, we will go through the details of the data capture stage and document classification with AWS AI services. We will also look into the details of AWS AI services such as Amazon Comprehend custom classification and Amazon Rekognition for document classification.
