Teqfocus
Know this before entering the ‘Real’ world of ‘Artificially’ Intelligent Data Processing
The application of Artificial Intelligence and Machine Learning (AI/ML) in a hyper-automated extraction-analysis-categorization process of high-volume documents is called Intelligent Document Processing (IDP).
The value proposition of IDP promises excellent benefits like a significant reduction in the time to process documents, reduced errors in processing, and reduced human intervention, resulting in ultimately increasing efficiency and efficacy.
Documents could be of various types, physical or electronic, and composed of structured, semi-structured, or unstructured data. An efficient and mature IDP platform should be able to process all such documents to enable the automation of business workflows and enterprise processes.
This high-growth market is getting overwhelmed by new entrants seeking to serve beyond the existing template-based OCR extractions to enhance their technology and market share.
With such new entrants, the market is becoming more and more competitive. Many of the IDP vendors are those with established brand names and market shares.
Hence, the new entrants must clearly understand the market to compete and penetrate the market effectively. Such new entrants must establish a platform that offers complete content processing, allows quick and easy setups, and allows customizations and processing of different varieties of content and data types.
They must empower semi/non-technical business users to implement changes as necessary and allow integration with the existing infrastructure of the clients.
Different types of IDP service providers may be typically categorized as follows:
1. Established or leading players who have (say) decades of experience in standard products and technologies like optical character recognition (OCR). It is much easier for them to navigate into upgradation of their systems for an IDP by gradual and structured implementation of AI/ML on top of their established platform. Their existing brand loyalty makes it easier for them to offer attractive deals.
2. New entrants or startups in the space of IDP services are usually venture capital-funded companies. Their key value proposition is their expertise in AI/ML approach, but usually, they lack standard offerings like OCR, for which they tend to partner with other players. Such service providers typically focus on semi-structured and unstructured data because of their AI/ML domain expertise.
3. Providers are usually the software vendors in some complementary or adjacent product. IDP is normally a complementary product for such vendors. Having IDP as their business offering will allow them to encroach on more markets and tap new businesses by offering a more comprehensive product offering. They usually start in the IDP domain by processing the structured data and gradually building capabilities to address semi-structured and unstructured data.
4. Finally, providers like independent consultants, system integrators and business process service providers exist. They usually have the expertise or a ready solution in some specific application of the IDP. Their solution can address document extraction and capture for that particular process but is usually not interfaced with any other process. They keep their focus on that specific process for many different companies.
