AI-powered prescription automation solution

Handwritten and printed text extraction

Doctors use everything from handwritten notes to digital files, and this inconsistency makes it tough to pull out clean, reliable data. Poor handwriting, different fonts, and mixed file formats often lead to missing details, mistakes, or processing delays. And when staff have to manually enter all that data? The risk of errors goes up, making the whole process slow and frustrating for the team.

Solution

We implemented a multimodal large language model (LLM) that can interpret both text and images. This turned out to be a great choice, as the created AI-powered solution could read scanned handwritten notes — even those with poor penmanship, process mixed-format documents, and extract structured data with high precision.

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Handling multiple prescription formats

When we looked into the local healthcare field, we found that medical documents came in all shapes and sizes. Doctors scribbled notes by hand. Hospitals printed forms with their own unique layouts. Digital systems generated PDFs with varying structures. And every region seemed to have its own way of organizing medical plans and paperwork.
These documents were often filled with tables and columns, and the lack of standardization made it tricky to know where important data was, how it was formatted, or how it should be interpreted. This posed a challenge for our AI-powered solution, which needed to read and unify all of these different document types accurately.

Solution

To tackle this, we trained our multimodal LLM using a wide variety of medical plans and forms.

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Data validation

Even with accurate extraction, there was still a big question: Is all the required info actually there? To generate a barcode that meets German healthcare regulations, certain data fields can’t be missing — otherwise, it could cause processing delays or even legal trouble. So we needed a way to catch any gaps before things moved forward.

Solution

Our experts implemented a validation step into the document generation process. It checks whether all the necessary fields are present and flags anything that’s missing. If something’s off, the system highlights the exact spot so the team can quickly fix it.