29.04.2021 | Blog Intelligent document analysis and processing

In the daily workflow, employees are constantly confronted with it: Enormous amounts of data are available and new data is constantly being added. How do they find the documents they need for their work from numerous sources? How do they quickly filter out the relevant information from these documents so that they can complete their tasks optimally? And is there a way to smartly automate parts of information-based business processes through intelligent data analysis?

Document intelligence is the key to all tasks that involve quickly recognizing and extracting relevant core information (also known as "insights") in any content and documents and using it to continue working. These search and analysis tools can be connected to all of the company's internal and external data sources and use the latest processes and methods of artificial intelligence. These include, for example, machine learning, deep learning, transfer learning and search technologies with an excellent understanding of language. This enables the software to recognize relevant core information in any document and content quickly, automatically enrich and refine it with metadata, and thus provide users with valuable insights for completing their tasks.

The software understands natural language search queries, i.e. entire sets of questions with the common W-questions (who, where, when, what...), summarized under the keyword Natural Language Processing (NLP). It enables employees to find information in a personalized way, depending on their area of responsibility. In addition, intelligent search and analysis software is able to recognize topics, automatically tag them, and extract them for further processing.

With these capabilities, the software can not only be used to quickly find relevant information in organizations, but it can also be integrated into any workflow to digitize, optimize and automate processes. Here are a few examples of how such a solution is used in practice in addition to the classic enterprise search use case.

• Application documents submitted via a customer or citizen portal, for example, are automatically checked for plausibility, formal correctness and completeness. Even during data input, applicants are notified if documents need to be corrected or supplemented.
   
• Document topics are identified and then used to sort documents. For example, incoming e-mails can be automatically categorized and routed for reply, or automatic replies with further information can be sent. Editorial departments also benefit, for example, from the ability to automatically classify topics and to tag new documents for news archives.
   
• Information relevant to data protection as defined by the GDPR can be located quickly and reliably. This allows companies to quickly respond to requests for information or clean up their unstructured file repositories of personal content such as job applications and resumes that does not belong there.
   
• It can locate particularly valuable content such as patents, inventions and other intellectual property. Companies can then fully protect this content from unauthorized access with appropriate security policies.
   
• Companies can identify documents and data that are subject to export control regulations. Then, for each individual piece of information, it can be determined in which countries it may be stored and to whom it may be disclosed.
   
• HR consultancies and departments can automatically identify knowledge and skills in resumes and match them with job profiles of open positions to quickly and reliably find suitable candidates.
   
• Key clauses and data points in contracts can be identified for a quick and reliable review of large contract portfolios, for example, in the event of legislative changes, company acquisitions or current events such as the Corona pandemic.
   
• For employees who need to keep up to date on current topics relevant to their work, web pages and documents can be monitored and any changes found can be displayed.
   
• New articles can be automatically assigned to the corresponding product categories. The software determines the product codes for data sheets or brief descriptions and creates a uniform metadata layer across the entire product landscape. This facilitates research and customer-specific product catalogs can be created, which customers can import into their ERP systems.

No matter for which scenario AI-based search and analytics software is used. It enables deep insights into an organization's data landscape, provides contextual information to its users and supports the automation of information-based processes.

Around this topic, the market research institute Gartner recently published its "Magic Quadrant for Insight Engines 2021". This report provides an overview of the insight engines market and current trends. IntraFind Software AG is once again included in this report, which focuses on 15 relevant global vendors.

The full report can be found at the following link: Gartner Magic Quadrant for Insight Engines 2021 | IntraFind