Interactive walkthrough

AI Document Processing, Step by Step

Pick a document type and what to check, run it, then choose what happens next — the same document processing pattern behind invoice processing and contract analysis, run against an example document with real numbers generated fresh each time.

What happens outside the chat window

Document upload
AI document processing
Extract fields
Validate against records
Human review
Update system
1

Document type

2

What should it check?

WALKTHROUGH

Run it to start — you'll get to choose what happens next, too.

Why this matters

The manual re-keying step — opening a PDF, reading it, typing the numbers into whatever system needs them — is where the document processing pattern earns its cost back fastest: the documents are already digital, the fields are usually in predictable places, and it's exactly the kind of repetitive work a person shouldn't be doing by hand at volume. The two specific shapes worth their own detail: 3-way invoice matching and flagging non-standard contract terms. See what actually costs money to maintain once a pipeline like this is running.

How this actually runs

Every run above — including each follow-up choice — is a real JSON-RPC tools/call request to tunovix.com/mcp. The invoice/PO numbers and dollar amounts are generated fresh on the server each time, so two runs won't look identical; nothing here uploads or reads a real file. What's real is the pipeline: fields get extracted, checked against existing records, and anything uncertain gets flagged for a human instead of silently pushed through. See RAG development for the retrieval layer this is usually built on.

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