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Background:
A large organization received numerous customer feedback forms and application documents through email or FAX. These forms were filled with critical data, including personal details, preferences, and service requests. The manual process of extracting this data and entering it into the system was time-consuming, error-prone, and inefficient.
Solution:
The organization implemented an automated system for processing scanned forms using Optical Character Recognition (OCR). When a form is received, the web server identifies the layout and coordinates of the fields using image processing techniques. The form is then partitioned into smaller sections, each corresponding to individual fields (e.g., name, contact details, service request). OCR software extracts text from each section, and the extracted data is presented to the user via a web interface for confirmation or correction. Once the user validates the information, it is stored securely in a database. A separate program then retrieves this data and applies predefined algorithms to generate reports (e.g., customer satisfaction analysis, service prioritization), which are displayed to the user or sent via email as PDFs.
Outcome:
This automated system reduced the time and effort spent on manual data entry, minimized human errors, and enhanced operational efficiency. It also enabled faster generation of reports, improving decision-making processes and customer service.
Client: Private Company , Germany