Document & PDF Automation Pack
8 workflows that get data out of PDFs, scans, and invoices and into a system you can actually query
What This Pack Does
Extracts text and structured fields from PDFs, scans, and invoices, stores them with embeddings, and answers natural-language questions about their contents with citations.
Who It's For
Operations and finance teams re-keying data from documents by hand, and anyone sitting on a document archive they cannot search.
Expected Outcome
Turn incoming PDFs, scans, and invoices into searchable, queryable data with no manual re-keying
Highlights
- Pipeline: Ingest → Extract → Structure → Store → Query
- Three grades of extraction: digital text, OCR for scans, structured fields for invoices
- End-to-end invoice processing from Gmail to Google Sheets
- Natural-language document querying with source citations you can verify
- Automatic summarisation of anything dropped into Google Drive
Included Workflows(8)
Extract
Structure
Store
Query
Setup Requirements
An n8n instance and OpenAI API key are the baseline. OCR needs a Mistral API key, document storage and querying need a Supabase project with pgvector enabled, and the invoice workflows need Gmail and Google Sheets access.
Example Use Case
A bookkeeping firm receives 400 supplier invoices a month as email attachments in mixed formats. The Gmail invoice workflow files them automatically; digital PDFs go through text extraction while scanned ones go through Mistral OCR; the structured extraction workflow pulls supplier, date, line items, and total into Google Sheets. Everything is stored in Supabase, so when a client asks what they spent with a supplier last quarter, the query workflow answers with citations pointing at the source invoices.
Primary Integrations
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