Organization documents comprise invoices, emails, tax forms, HR documents, contracts, images, PDFs, and much more. These documents are a treasure chest of information, which, if extracted wisely, can add incredible value to business processes. Due to their unstructured data, much of the granular insights remain untapped in the absence of proper tools for extraction.
Document AI replaces the manual process of document ai and data extraction to reach deeper and unearth hidden insights faster than humans.
What is Document AI, and How does it Help with Data Extraction?
Document AI, commonly known as Document Intelligence, utilizes Natural Language Processing, Machine Learning and other capabilities to train machines in extracting document data like humans.
It is tasked with transforming unstructured data into consumable information through content classification, entity extraction and advanced searching. Document AI converts images to text, classifies documents, and analyzes and extracts entities.
Document AI digitizes paper-based documents in the shared cloud space. It leverages a combination of the latest tech-based solutions such as Intelligent Character Recognition, Optical Character Recognition, Natural Language Processing, character and word recognition, and others to identify and extract text from different document types.
Businesses deal with hordes of documents daily, and each document, be it a PDF or an image, is a treasure chest of valuable data. But extracting such granular insights manually is never a feasible approach. It is both time and labor-intensive and prone to mindless errors. AI document processing addresses the time and labor-intensive factors aptly and extracts actionable insights to add value to the organization.
The following are a few benefits to consider: –
- The primary purpose of document processing automation is to use deep learning capabilities for processing files independently. Further, it generates forms and offers embedded templates so that users can add data directly without following the lengthy process of finding relevant files and entering information manually.
- Document AI identifies, labels and organizes files under specific categories after digitizing documents to help businesses locate critical data in the expected folders and extract information when needed, where needed.
- Again, using deep learning capabilities, AI documents tags documents and files and organizes them under specified groups faster than humans, minus errors. It reduces manual efforts and accelerates data processing.
- It scans documents and extracts critical data, making it valuable in a few seconds.
- Document AI caters to text, character, and image recognition in more than 200 languages with utmost accuracy using deep learning and OCR techniques. It can understand professional jargon, intent, and sentiments behind such content.
Document AI Applications and Use Cases
Document processing automation is applicable in various industries that work with paper-based or digital documents daily. Processing documents in bulk and extracting information for decision-making is a long-haul procedure. It is not feasible to keep resources solely for document processing and data extraction for many reasons.
Firstly, the time-intensive repetitive task eats away valuable productive hours preventing the resources to utilize their skills elsewhere optimally.
Secondly, data are often not available just when needed or might be missing out on some granular information. Also, manual data extraction is subject to human errors, reflecting a wrong picture and impairing decision-making.
Thirdly, the time-intensive task can exceed the time needed to process documents and unearth hidden opportunities.
Fourthly, this approach increases employee disengagement, leading to high turnover rates.
Hence, leveraging AI-based solutions for the same is worth the time, money and effort spent.
Here are a few use cases for Document AI: –
Accelerating Documents Processing for Mortgage
Loan applications are time-intensive and complex procedures, entailing a horde of customer documents to be processed for data extraction. Document AI automates the whole process of routine document reviews, sparing mortgage providers to focus on other value-added services.
Automating Procurement Data Capture
The procurement cycle is driven by a colossal number of documents in various formats exchanged between procurers and suppliers. Such document types include invoices, money receipts, contracts and others. Each of these documents contains enormous datasets, which can benefit businesses in the future. Document AI automates the whole process of receiving records in various formats, digitizing and categorizing them, and returning cleanly structured data.
Accelerating Contract Lifecycle Management
Contracts are legal documents containing various terms, conditions, and clauses of immense interest to the parties concerned. Most companies hire legal teams to scan through every page of the contract and every line of the clause to capture minor variations in the terms and conditions. And, it is not just about one single contract. Large enterprises have to process contracts in bulk daily. Document AI automates the whole process with the help of NLP, knowledge graph technology, and optical character recognition (OCR) to accurately extract essential information accurately and faster than the legacy-manual approach to document processing.
Document AI is the New Normal for Data Extraction
And quite rightfully so!
Massive advancements have been made in ML, AI, NLP, Computer Vision, and similar technologies to help software accurately emulate human behavior, like extracting information from documents.
Document AI is one such technology solution that proved to be game-changing for businesses and a blessing-in- guise for employees. It made scanning boxes of documents and highlighting sections a thing of the past.
This technology marked the dawn of a new era where processing bulk documents will no longer be a pain for organizations and their resources.
