Usually, organizations have different kinds of needs, which in most cases are unique when requiring the processing of documents.

This makes it difficult to clearly identify customized requirements for intelligent document processing (IDP) solutions.

Documents in the stores of an organization contain a trove of useful data and a heap of useless data.

From such documents, valuable information and insight need to be derived, which can help the organization and the Managers to automate and improve their decision-making toward integrated business growth.

Applications of the technologies like natural language processing and computer vision in IDP mines the data, useful for process automation and analysis.

There are many varied and overlapping choices of IDP vendors, and their selection becomes critical if the core requirements are not clearly defined and understood by the business leaders.

The three core requirements while creating a request for proposal for an IDP solution are Document format variation, Analytics vs. Automation, and Enterprise vs. Local requirement.

There is usually a spectrum of use cases the organizations would need to leverage for IDP.

The data consumed by such use cases could be: Structured (e.g., standard official forms collecting data in a specified format); Semi-structured (e.g., invoices, purchase orders, and contracts where the data is not in a strictly standard format); and Unstructured (e.g., images, news articles, audio/video files, etc.).

After the data is extracted from such documents, it is necessary to have a contextual understanding before classifying the data as per the organizational requirements. Sometimes, a specialized IDP or deep natural language understanding capabilities may be a need based on the specific use case.

Hence, document-format variation is a key attribute to understand when selecting an IDP tool.

When organizations want to derive insights from content and use it for further analytics or when there is a need to work with diverse content types, there may be a need for specific IDP capabilities called multimodal analytics.

Such specialized IDP vendors will focus on automation or BPM capabilities and will eventually evolve into content processing and semantic platform or will offer deep analytics.

Finally, it is also necessary to understand whether the IDP application is enterprise-wide or limited to certain departments.

For an enterprise-wide application, IDP should offer building blocks for a variety of use cases by providing capabilities from adjacent technology areas such as natural language question and answer (NLQ&A).

However, in the case of a department-specific use case, a packaged application tailored to the business process should be selected.

Written language processing capabilities, industry/domain-focused capabilities, prebuilt services, and low/no code capabilities are additional considerations for IDP vendor selection.