Data integration plays a crucial part for a lot of work process in all companies, a lot of the times companies would need to deal with a large quantity and variations of documents to process. Therefore Intelligent Document Processing (IDP) can provide significant help in terms of improving work productivity and efficiency during data integration.

What is Intelligent Document Extraction?

Intelligent document extraction is a part of IDP. It helps companies to process documents with technologies such as Machine Learning (ML) and Natural Language Processing (NLP) in extracting or storing data as efficiently as possible. 

The concept of intelligent document extraction is getting the data. Usually, in a traditional way, this process relies manually on human staff. Human staff would need to collect data from various sources, it may vary from paper documents that need further scanning, or scanned documents in computer. Next, human staff would need to manually get data from those documents and place in spreadsheet, to be further entered into a system (e.g., ERP system). However, this method is no longer desired considering that there may be hundreds of documents to process each day. It would be overwhelming and time-consuming for human staff to do document extraction and processing as well as data integration on systems manually. This will keep human staff away from doing other tasks that are more strategic and value-added.

In addition, a lot of times the data comes from documents that are unstructured or semi-structured, making it very difficult to manually collect data. With Intelligent document extraction, companies can easily read, extract and organize data from these kinds of documents. We can have cognitive bots to scan our paper documents, converting it into a digital data that is readable for the machine. Then, cognitive bots read the documents to identify which data fields to extract. Cognitive bots will place the extracted data into a spreadsheet, or directly enter it into the system (to make new data entry or update exisiting data). With this ability, intelligent document extraction will help the process of data integration, saving human staff from doing mundane and time-consuming tasks so they can focus to tasks that bring more value for the enterprise.

Read more on Intelligent Document Processing: 3 Reasons Why Intelligent Document Processing Makes Your Insurance Company Productive

What are the technologies in Intelligent Document Extraction?

Extraction of information or data from multiple documents is the most prominent capability of AI, especially machine learning and natural language processing (NLP). Intelligent document extraction allows the automation of data movement from multiple documents into spreadsheet. This capability has remarkable advantages such as faster and easier with lesser error (compared if done by human-staff) which explains why it is the most prominent and commonly used application of AI combined with RPA.

Intelligent extraction involves various of AI tools that can support the accuracy of data extracted:

  • OCRHelps by converting any images containing written text into digital data that is readable by the machine.
  • Machine LearningTraining the machine to understand the pattern and trend from set of data, so it will be able to do extraction of specified information from incoming documents. Machine learning can be done on both structured and unstructured data.
  • Natural Language Processing (NLP)Helps machine to interpret sentences and paragraphs of continuous text written by humans to be further processed thus improve extraction. NLP helps to identify specified information to be extracted from documents. With NLP, the intelligent extraction can be done in multi-languages (English, Chinese, Indonesian, Vietnamese, Japanese, etc.).

The process of intelligent document extraction is as following:

The process of intelligent document extraction

What are the benefits of Intelligent document extraction in data integration?

There are a few benefits when it comes to utilising Intelligent document extraction:

  1. Save time: Using Intelligent document extraction and other IDP procedure can help workers automate large volume of workload, resulting improvement in efficiency, more man-power hour saved.
  2. Save cost: Due to the decrease in required time and man-power to process such task, this will result in the reduction of labour costs and operational costs.
  3. Scalability: Intelligent Document Extraction can easily by implemented in multiple applications and systems, this can further improve work efficiency across companies.
  4. Ensure accuracy and quality: By incorporating Intelligent Document Extraction, this can eliminate human-made-errors while improving data quality and  high accuracy.

How can Gleematic help with automated data extraction?

Gleematic AI Cognitive Automation have helped many companies across various industries with data extraction. Using our software, user can easily implement Intelligent Document Extraction without needed any coding knowledge. Our Gleematic bot already have the technologies such as OCR, multi-language NLP, Machine Learning etc. in order to intelligently extract data.

Datas can be automatically organised into designated file formats such as PDF or Excel Sheet. When there are inaccurate/inconsistent data, it will be flagged and human would be alerted to complete the final validation of the data. This means that Gleematic bot will not replace office workers but to help and empower them.

Extract Data from Invoices with Different Templates in 10 Minutes with Gleematic

This demo video shows how Gleematic can extract data from 10 invoices with different templates. Each invoice has different positioning and formatting, it may be hard to extract data from using an extraction tool. But with Gleematic, everything is possible!

Check out more of our Gleematic AI use cases with Intelligent Document Processing:
Cognitive Automation for Purchase Order Reporting in Manufacturing
Cognitive Automation for Container Booking in Logistics

Written by: Reiko Anjani and Kezia Nadira