In the world of data management and computational linguistics, a relatively new buzzword has been making the rounds—“intelligent document processing” (IDP). Defined in simple terms, intelligent document processing utilizes artificial intelligence, machine learning, and natural language processing to capture, process, and interpret information from unstructured and semi-structured documents.
Traditional automation tools are effective at processing structured data (data in fixed fields like in spreadsheets), but the vast majority of data in most organizations isn’t structured. Herein lies the significance of intelligent document processing: it transforms unstructured data into a structured format, ready for analysis and decision-making, helping businesses undergo complete digital transformations.
Intelligent document processing helps to considerably diminish manual intervention, making data processing more efficient, accurate, and speedy. It also assists organizations in making the shift to digital with ease and can reveal previously hidden insights and patterns that would otherwise be unnoticeable with traditional extraction methods.
On a larger scale, multiple industries are benefiting from intelligent document processing solutions. In banking and finance, documents like loan applications and customer account forms are processed more quickly and accurately, significantly reducing processing costs while increasing customer satisfaction through faster service. In healthcare, intelligent document processing is being used to digitize patient records, making healthcare more personalized, efficient, and safer.
With intelligent document processing, businesses can automate processes that include the ingestion of unstructured data. Intelligent document processing is a broad technology category that includes intelligent intake, which enables companies to automate the processing of virtually any kind of content, including emails, for processes such as insurance claims and underwriting, customer onboarding, and mortgage processing. Intelligent document processing automates the initial reading and categorization of documents as well as the extraction of key data, dramatically reducing document intake time while improving accuracy.
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Intelligent document processing solutions are built using tools like AWS and Microsoft IDP to read, interpret, and classify complex, unstructured information like invoices, contracts, emails, etc. These tools can often interface with, or even be written in, programming languages such as Python, which can include libraries and frameworks catering to intelligent document processing, making them more effective.
Stepping into the spotlight in the Intelligent document processing arena is Indico Data. Unlike other intelligent document processing companies that focus mainly on structured documents, Indico Data specializes in reading and organizing unstructured data. This, in turn, has been key in setting the tone for the company’s innovative and distinctive services within the intelligent document processing market.
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In conclusion, the value proposition of intelligent document processing is astronomical, and it’s apparent that companies like Indico Data have strategically positioned themselves to ride this wave of digitization. The industry has seen great growth in recent years, and in many ways, this technology is still in its early days. It would be no exaggeration to say that the future of data management and digital processing is likely going to be formed by intelligent document processing, embracing unstructured and structured data together.
