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$20

AI Document Processing

Build a document processing pipeline that extracts text and tables from PDFs, classifies document types, pulls structured fields, validates data quality, and outputs clean structured data.

"Extract the vendor name, invoice total, and line items from these 50 invoices — with 98% accuracy"

6 Interactive Sessions

Short, interactive sessions — watch it work, steer it, then build it yourself. Go deeper anytime with the full code walkthrough.

  1. 1

    The Messy Stack — turn every doc into structured text

    Before you can classify or extract anything, every document has to become structured, machine-readable text — tables and all. A human keying 50 invoices is slow and makes mistakes; step one is turning each one into a consistent schema.

  2. 2

    What Kind of Doc Is This? — type before fields

    You can't extract "invoice total" from a document that's actually a purchase order — the fields you look for depend on the type. So before extraction, classify the document and attach a confidence to the guess.

  3. 3

    Pull the Fields — three shapes, three strategies

    Now turn the structured document into data: vendor name, invoice total, line items. Three different shapes on the page need three different strategies — and each field comes out with a confidence and a source, so you know how it was found.

  4. 4

    Is It Right? — the path to 98%

    The extractor says the total is $4,200 — but the line items sum to $4,020. Something's wrong. Validation is what catches it: schema checks, cross-field rules, and routing anything low-confidence or inconsistent to a human. That's how you reach 98%, not by trusting raw extraction.

  5. 5

    Extract, Review, Export — the human reviews, doesn't re-key

    The human's job shrinks from keying every field on all fifty invoices to reviewing the handful the pipeline flagged. The app shows each doc with its fields boxed on the page, highlights the uncertain ones, lets you fix them, and exports. Fifty invoices in minutes.

  6. 6

    50 Invoices, Every Day — the production flywheel

    Fifty invoices today, five thousand next quarter. Production isn't a bigger demo — it's watching accuracy over time, a review queue that feeds corrections back into the extractors, retraining when a new vendor format appears, and enough throughput to keep up.

Production patterns you'll master

Text ExtractionTable DetectionField ExtractionData ValidationObservability

Synthetic data included

  • Invoice PDFs (200 invoices)
  • Contract documents (50 contracts)
  • Receipt images (100 receipts)
  • Form templates (JSON)
  • Validation rules

What you walk away with

Shareable portfolio

A public URL showing your module timeline, patterns mastered, and completion status.

All the code

Download everything as a ZIP — pipelines, guardrails, deployment configs. Yours forever.

Module walkthrough

Each module documented with deliverables and the production pattern you implemented.

Ready to build your ai document processing?

First course free. $20 per course after that.