Shortcuts to the project
The starting point was a recurring media discontinuity: questionnaires were available in paper form, but further processing needed to be transferred more efficiently into digital workflows. We were looking for an approach that would complement existing processes rather than creating new manual intermediate steps or additional interfaces. Our goal was a flexible solution that integrates seamlessly into the existing system landscape. Instead of introducing an additional application, we designed the solution as a background service. It processes incoming form scans, organizes recognized data in a structured manner, and can be integrated into existing applications. This resulted in a production-ready service for automated form recognition and questionnaire evaluation. The guiding principle here: AI handles the complex analysis, while traditional software logic ensures stability, scalability, and cost-effective operation.
These are the benefits of AI-powered form analysis
Less manual work
Recurring steps in the processing of paper-based questionnaires can be automated.
Faster availability of results
Responses and relevant information can be processed more quickly and made available for further use.
Improved scalability in operation
We designed the architecture to support additional form variations.
Seamless integration into existing processes
The service runs in the background and complements the existing digital infrastructure without requiring an additional user interface.
Cost-effective use of AI
AI is used specifically where it is technically necessary. Standardized steps are handled by traditional software logic.
Greater security for future development
Realistic test forms helped to systematically evaluate the solution's quality, stability, and scalability.
From a manual process to an integrable service
A step-by-step approach was key: First, we assessed whether AI-based form recognition was suitable for the specific use case. We then refined the approach and used a specific form to develop it into a production-ready service.
An important lesson learned was striking a balance between AI and traditional software development. Not every processing step had to be solved by AI. For repeatable tasks, we deliberately relied on traditional logic, while we used AI where recognition and interpretation were more technically challenging.
The result was a cloud-based service that combines AI components with traditional backend logic.
What role AI plays in processing
AI is particularly useful when scanned forms need to be interpreted: in recognizing the form, capturing completed fields, and extracting relevant information. The information is then formatted so that it can be processed further in existing applications.
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