OCR and AI: Intelligent document processing
“Classic” Optical Character Recognition (OCR) has already been used for many years - AI-based document processing methods create completely new perspectives: far higher recognition rates, automation of complex processes and significantly greater efficiency.
OCR text recognition and artificial intelligence
The digitization of numerous business processes is not possible without structured evaluation of information from documents. Where systems previously reached their limits, OCR with AI technology makes it possible to evaluate even long and complex documents in a structured manner. Information can thus be read not only from standardized documents such as invoices - even contract information or scientific publications can be analyzed and the information extracted.
Integrated individually and strategically into the process landscape, the use of OCR with AI technology enables companies to automate processes, increase efficiency, reduce the error rate and create a valuable database for strategic decisions.
Processes when using OCR with AI technology
Perfectly integrated into the existing IT environment and adapted to subsequent processes, OCR with AI technology ensures the initial classification of incoming documents - or even the basic analysis of large volumes of inventory documents. The software then extracts the required information using “Contextual AI”.
Here, the AI recognizes information in context - regardless of the structure of the documents or specific wording. The information can then be compared with existing data (e.g. in the ERP or CRM system) and, of course, checked and corrected if necessary. Subsequently, the software for OCR with AI initiates workflows individually tailored to the process and transfers the data.
The following is the basic process when using the AI software kinisto from tetrel:
Massively accelerated inbound management
Automation of previously manual activities
Automation of complex processes
More efficient processes
Faster processing
Higher accuracy
Compliant
Quickly ready to use
Workflow automation
Application areas of OCR and AI-based document processing
OCR has already been used in companies for some time - especially for reading data from invoices. Here, the systems are already quite mature in some cases, as invoices in particular are the most widely standardized documents in companies. By using AI technology, recognition rates can be massively increased once again, as information is recognized regardless of layout. A level of automation up to complete dark processing can be achieved.
Intelligent document processing solutions are particularly worthwhile where reading text requires manual effort. AI technology makes it possible to find information in long, complex documents. In practice, this primarily means time savings, but also greater transparency, lower error rates and better scalability. In contrast to OCR, AI software can be integrated into complex processes on the document to complete partial work steps. This is the case, for example, when checking contracts for certain risk clauses or when matching job application documents with the required skillset.
Intelligent Document Processing (IDP) solutions also enable the rapid extraction of information from large volumes of documents. For example, the entire contract portfolio of insurance companies can be quickly checked for specific content. AI thus makes information that is already available but was previously “hidden” usable.
Classic OCR processing and OCR with the latest AI technology
It quickly becomes apparent that the classic OCR process can neither achieve the accuracy nor the scalability of AI-based document processing. Layouts change over time, and new documents with previously unknown structures are added. Keyword-based text rules are also rarely unique. AI-based processes, on the other hand, recognize these cases through “real” language understanding, regardless of the exact wording in the text.
OCR and AI document processing in comparison:
| Possibility | OCR | KI |
|---|---|---|
| Keyword search | ||
| Position based recognition | ||
| Processing without position templates | ||
| Processing without manual rules | ||
| Recognition of information in linguistic context | ||
| Processing of previously unknown formulations without adaptation | ||
| Processing of previously unknown layouts without adaptation |
In principle, an AI-based document processing system can perform tasks that would otherwise be performed by a student worker - i.e., classifying or extracting information according to clear specifications.
From template to human level reading
Document processing using classic OCR
Optical Character Recognition (OCR) initially has nothing to do with AI. The classic method for automated document processing has existed since the 1970s1. It is based on the recognition of information that is located by default at a certain position in the document. Rule-based, an attempt is made to recognize the correct information on the basis of the page layout or individual keywords. For example, a five-digit number can be recognized as a postal code and the word after it as the associated city.
In terms of implementation, this means that specific rules (known as templates) must be created for each layout and each possible formulation. Without the appropriate layout for the document type, no recognition of information is possible. The limits of OCR are thus quickly reached, in contrast to the AI-based solution. After all, a five-digit number can be not only a postal code, but also a sum of money.
AI-based document processing
Unlike OCR: AI-based solutions for intelligent document processing allow information to be read at a human level - only faster and more accurately.
OCR is used here only for the purpose of pre-processing. In other words, for the initial recognition of text in scanned documents. However, the AI-based software then also recognizes the meaning of the text modules and establishes their relationship to one another - both linguistically and in terms of their position in the document. This makes it possible to capture complex content relationships, regardless of wording, structure, layout and format.
The role of OCR and AI in digital transformation
We are at the beginning. The possibilities that intelligent document processing solutions offer companies are far from exhausted. The use of AI technology is not only worthwhile for corporations; smaller and medium-sized companies can also sustainably make processes more efficient, relieve employees, reduce error rates and work more economically thanks to the new technology. Intelligent Document Processing will permanently change the way we perform our daily tasks in connection with documents and text.
The system for document analysis
With kinisto, tetrel offers an individually configurable AI system for Intelligent Document Processing - based on Natural Language Processing (NLP) with Deep Learning methods. kinisto can extract complex, individually defined information from documents of any kind.
Where business and technology intertwine, tetrel uses artificial intelligence to optimize and accelerate everyday work and background processes. As a specialist for AI technology in practical use, we would be happy to advise you on the topic and your specific case!
