Software:Document AI
Document AI, also known as Document Intelligence, refers to a field of technology that employs natural language processing (NLP) and machine learning (ML) techniques[1]. These techniques are used to develop computer models capable of analyzing documents in a manner akin to human review.
Through NLP, computer systems are able to understand relationships and contextual nuances in document contents, which facilitates the extraction of information and insights. Additionally, this technology enables the categorization and organization of the documents themselves.[2]
The applications of Document AI extend to processing and parsing a variety of semi-structured documents, such as forms, tables, receipts, invoices, tax forms, contracts, loan agreements, and financial reports.
Key Features
Machine learning is utilized in Document AI to extract information from both digital and printed documents. This technology recognizes text, characters, and images in various languages, aiding in the extraction of insights from unstructured documents. The use of this technology can improve the speed and quality of decision-making in document analysis. Additionally, the automation of data extraction and validation can contribute to increased efficiency in document analysis processes.
Common Uses
- Enhancing the reliability of business information by reducing manual data entry errors
- Utilizing AI to identify anomalies in new invoices from established customers
- Accelerating the mortgage workflow process
- Automating the monitoring of loan portfolios for credit risk management
- Enabling employee focus on higher-value tasks
- Detecting counterfeit currency and fraudulent checks
- Extracting and analyzing data previously inaccessible in document silos for informed business decisions
- Streamlining the processing of receipts on a global scale
- Assisting firms in automating the assessment of regulatory change impacts on contracts
- In the real estate sector, aiding in developing standardized document classification and automated information extraction[3]
References
- ↑ Cui, Lei; Xu, Yiheng; Lv, Tengchao; Wei, Furu (2021). "Document AI: Benchmarks, Models and Applications". arXiv:2111.08609 [cs.CL].
- ↑ "Why Digitizing Documents has been Accelerated by COVID-19 Pandemic". 15 January 2021. https://www.eweek.com/enterprise-apps/why-digitizing-documents-has-been-accelerated-by-covid-19-pandemic.
- ↑ Bodenbender, Mario; Kurzrock, Björn-Martin; Müller, Philipp Maximilian (April 2019). "Broad application of artificial intelligence for document classification, information extraction and predictive analytics in real estate" (in en). Journal of General Management 44 (3): 170–179. doi:10.1177/0306307018823113. ISSN 0306-3070. http://journals.sagepub.com/doi/10.1177/0306307018823113.
![]() | Original source: https://en.wikipedia.org/wiki/Document AI.
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