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Azure PDF Date Extractor App with error handling UI

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placeGB home_workRemote assignmentBefristet publicAggregierter Job · GB

eventVeröffentlicht am 14. Sept. 2026 · verifiedWir haben am 16. Sept. 2026 bestätigt, dass er noch aktiv ist

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£ 10 – £ 20 pro Projekt

Über den Job

I need a small-footprint Azure application, that I can deploy inside my tenant, that lets users upload a PDF of our “date effective” records and automatically pulls out the From Date and To Date. Here is the flow I have in mind: 1. Upload interface (simple web page or BLOB-triggered function) accepts a single PDF at a time. 2. Azure AI Document Intelligence handles the parsing. If extra text cleanup or disambiguation is required, feel free to chain Azure OpenAI behind it. 3. Your code pinpoints the first instance of the two labels (“from date” / “to date”) and captures the values in ISO format. 4. The result, together with a unique identifier we generate for that file, is inserted into an Azure SQL Database table. I will provide sample PDFs and the target table schema (id, file_name, from_date, to_date, raw_json). Success means each sample lands in the table with correct dates and zero malformed rows. A short README template that recreates the resources round out the hand-off along with a recorded video call walking through the test and architecture. UI for end user error handling using Entra ID as authentification, how much extra will it be? UI Erorr handling as a Traffic Light Status Model with Entra Authentification Use a very visual status model throughout the journey showing a table of files processed with the following icons: [GREEN] Processed Successfully Document extracted Validation passed Record updated [YELLOW] Review Required AI confidence below threshold Missing mandatory fields Potential duplicate record Business rule conflict [RED] Action Required Corrupt file Processing failure Authentication issue System integration failure This immediately tells users where their attention is needed, with a processing button, send to DB, Update, delete.

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