Scenario: Data extraction pipeline — CCA-F Exam Prep

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L3.21|Scenario: Data extraction pipeline
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Two approaches
Split screen. Left: a desk buried in paper -- invoices, contracts, medical forms, emails printed out, sticky notes everywhere. A person manually typing data into a spreadsheet. Right: the same documents flowing through a digital pipeline, each step labeled (Extract, Validate, Normalize, Store), emerging as clean JSON on the other side. Modern, clean illustration.

10,000 documents arrive every day. PDFs. Emails. Scanned forms. Handwritten notes.

An insurance company processes claims. Each claim is a stack of documents: a PDF form from the patient, an email from the doctor's office, a scanned receipt, sometimes a handwritten note. All of this needs to become structured data in their system.

Today, 45 people do this manually. Average processing time: 12 minutes per claim. Error rate: 4%. The company wants to automate 80% of claims with AI, keeping humans for the complex 20%.

The pipeline: documents in, structured JSON out. Four steps. Error handling at each one.