Everyone has been there. In front of a scan invoice, purchase order or tax-related document, unsure of that tedious data entry is ahead. It is commonplace for Optical Character Recognition (OCR) Syansoft technology, though an improvement over manual input, can be a stumbling block when faced with the reality variation of such important documents for business. Uneven formatting, different layouts and smudged text – and the list continues. What if the OCR engine was able to learn? How would it adjust on the fly to the specific features of every type of document and become more intelligent with each document it reads? That’s the hope of the ability to train OCR engines. They could be a game changer for companies struggling over bottlenecks in document processing.
The Limitations of Legacy OCR: The traditional OCR is based on rules that are predefined and templates. While they can be useful for documents that are standard however, they are often unable to cope with the diversity inherent in documents used in business:
invoices : Variable layouts between companies, varying table layouts as well as inconsistent positioning of crucial information such as the invoice number and the total can cause confusion in strict system.
Purchase orders (POs): Similar problems arise when it comes to POs when different departments or suppliers could use distinct format. Finding crucial information such as quantity codes, item codes and prices can be a difficult task.
Tax Forms: The Tax Forms even if they are from the same country are often complex in their structure and precise field positions which require exact recognition. Tax documents from abroad introduce higher levels of variability.
What does this mean? The result? Manual intervention, mistakes in the process, delays and, ultimately the increase in operational cost.
Enter the Era of Trainable OCR: Trainable OCR engines utilize the capabilities in Machine learning (ML) as well as deep learning (DL) to break through these shortcomings. Instead of basing their decisions on rigid rules, they are able to are taught by the examples. This is how they do it:
Data as the Teacher: You feed the engine with an assortment of invoices, POs and tax documentation.
Feature Extraction: The engine intelligently recognizes important features in the documents, such as the layout, text patterns visual clues, as well as relations between different elements.
Model Training: sophisticated algorithms which train the machine to connect these elements with certain fields of data (e.g., “Invoice Number” is always displayed near the logo of a specific brand and follows an established pattern)
Continuous Improvement: The more information the engine is processing is the more precise it gets. It adjusts to changing designs and changes instantly which reduces the requirement to make manual adjustments.
- Real-Time Adaptation: The Ultimate Advantage: The “real-time” element is vital. Training is a must. OCR engines don’t have to be taught once, they frequently incorporate feedback and gain by examining new documents while they process them. This means that:
- Handling Unseen Variations: When a new invoice with a new design is received, the software is able to analyze it, find crucial patterns, and usually get the information it needs regardless of whether it’s previously seen the exact layout before.
Dynamic Field Identification: The engine is able to effectively locate fields, even if they shift slightly in position between one document and the following. - Contextual Understanding:
Advanced and trainable OCR may even utilize context-related information to enhance the accuracy. It is for instance, recognizing that a number followed by the “$” symbol is probably to be a price.
Benefits That Go Beyond Automation
Utilizing an capable of training an OCR engine to your invoices, POs, as well as tax-related documents can bring a myriad of benefits.
Increased Accuracy: Less errors when compared with the manual entry of data as well as conventional OCR.
Significant Time Savings: Automation allows employees to use their valuable time to concentrate on other tasks.
Improved Efficiency: Processes for invoices are faster as well as POs and tax returns.
Lower Operational Costs: The reduction in manual work and the fewer errors can translate to substantial cost savings.
Enhanced Data Quality: Accurate and reliable information can help you make better choices and be more compliant.
Scalability: It is easy to handle the increasing volume of documents, without requiring a lot of manual work.
Improved Compliance: The timely and accurate processing of Tax Documentation lowers the possibility of penalty charges.
The Future is Intelligent Document Processing.
The ability to train OCR engines are the leading technology in intelligent document processing (IDP). Through combining OCR and the capabilities of AI Companies can go beyond data extraction and gain a complete understanding of the document as well as automation Get In Touch.