GigaOm Radar for Intelligent Document Processing (IDP)v3.0

1. Executive Summary

Intelligent document processing (IDP) solutions enable the transformation of documents (both paper and electronic) containing unstructured, semistructured, and structured data into digital assets quickly and accurately. IDP solutions use AI/ML, plus natural language processing (NLP) and deep learning, to improve data extraction accuracy and enable faster processing.

IDP solutions involve pre-processing and post-processing stages: the first primes the document in terms of shape and size, and the second ensures that a substantial degree of accuracy in processing unstructured data can be achieved.

The availability of AI/ML/NLP capabilities in IDP ensures that the strike rate in processing data is significantly higher than what a mere optical character recognition (OCR) tool can deliver. AI/ML/NLP features have self-training, self-learning capabilities that lead to continuous improvement in the accuracy of processing all types of documents.

Prebuilt AI/ML capabilities and business rules enable automated verification and validation of data as well as continuous learning and improvements based on AI/ML algorithms and user input. IDP combines OCR, data capture, and AI/ML to automate the retrieval, understanding, and integration of documents required for executing a business process. Know your customer (KYC), invoice processing, insurance claims, patient onboarding, patient records, proof of delivery, bills of lading, and commercial order forms are some of the key use case processes and document types suited for IDP solutions. IDP can also be useful for industry-specific processes, such as customer onboarding, mortgage processing, financial trading, and legal proceedings. Some of the key buyers of IDP solutions are leaders in a variety of business areas: shared services, process automation CoE, global business services (GBS), digital transformation, and finance.

Decision-makers will want to determine the specific requirements of their organization to use as a baseline for assessing the features they need in an IDP solution. Some solutions offer prebuilt processes supporting specific industries, which can speed the implementation of the solution. In contrast, some IDP solutions offer a template-free approach and can be trained on new document types and layouts by using sample documents; such solutions will usually deliver greater value at a lower cost. IDP solutions should be adopted as part of a broader enterprise automation strategy in which suitable software products are used for meeting various task, process, and document automation requirements.

There are more than 60 vendors that provide IDP-type capabilities. In this GigaOm Radar report, we focus only on vendors with a noteworthy footprint in terms of scaled IDP implementations for which the IDP product involves more than an add-on to a broader robotic process automation (RPA) or intelligent automation platform. We excluded vendors whose solutions were more service based as well as those that offer basic OCR-based document capture without significant advancement in AI/ML capabilities.

This is our third year evaluating the IDP space in the context of our Key Criteria and Radar reports. This report builds on our previous analysis and considers how the market has evolved over the last year.

This GigaOm Radar report examines 18 of the top IDP solutions and compares offerings against the capabilities (table stakes, key features, and emerging features) and nonfunctional requirements (business criteria) outlined in the companion Key Criteria report. Together, these reports provide an overview of the market, identify leading IDP offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.