AI data extraction from documents and PDFs, straight into your ERP
AI data extraction reads a document the way a person would, finds the fields that matter, and returns them as structured data. For a manufacturer or distributor, that means customer POs, supplier invoices, spec sheets, prints and production sheets become ERP records without anyone retyping a line. Structify builds the extraction, the checks against your ERP, and the review step a person signs off on.
New to the topic? Start with unstructured data extraction, explained.
The documents your team retypes today.
Most of the paper that slows a plant or a warehouse falls into six kinds. Each has fields the ERP already expects.
| Document | Arrives as | Fields pulled | Lands in |
|---|---|---|---|
| Customer purchase orders | PDF attachments, email bodies, portal downloads | Customer, PO number, part numbers, quantities, prices, ship-to, requested dates | A sales order in the ERP |
| Supplier invoices and packing slips | The AP inbox, supplier portals, scanned paper | Invoice and PO numbers, line items, quantities, unit prices, freight, terms | AP, matched against the PO and the receipt |
| RFQs and parts lists | Emails with prints, models, or a BOM spreadsheet attached | Material, quantities, tolerances, finishes, due dates, every part number | A structured quote request |
| Engineering prints and spec sheets | PDF and CAD prints, including scans | Dimensions, tolerances, notes, flagged critical characteristics, material specs | The control plan and the item master |
| Production sheets and paper forms | Clipboards on the floor, retyped into spreadsheets later | Lot and batch, weights, times, checks, operator sign-offs | Production records you can query |
| Archived reports and logs | Decades of PDFs from different tools, some handwritten | Header metadata and the detail rows inside each report | One dataset with a single standard structure |
Five steps from the inbox to an ERP record.
- 01
Collect
Documents are picked up where they already arrive: the AP inbox, a sales mailbox, a shared drive, a supplier portal, the scanner by the receiving dock. Nobody forwards anything to a new tool.
- 02
Read
The model reads layout, tables that run across pages, stamps and handwriting, and transcribes what is on the page. The rule we build to: it never computes, converts, or invents a value. The math happens later, in tested code.
- 03
Check against the ERP
Every field is checked against the record it claims to match: the PO exists, the part number is real, the price is inside your tolerance, the quantities reconcile with the receipt.
- 04
A person reviews the exceptions
Documents that pass every check are previewed and posted. The rest go to a review queue with the reason attached, so a buyer or AP clerk fixes one field instead of retyping the document.
- 05
Post with narrow permissions
Writes reach the ERP through scoped, approved permissions, with read-only access by default. Corrections are kept, so the same fix is not made twice.
Why PDFs are the hard part.
A PDF looks like a document to a person and like a bag of characters, or a picture, to software. These are the five things that break PDF data extraction in practice.
Scans and phone photos
A scanned PDF has no text layer, only pixels. The page has to be read as an image, skewed and stamped as it is, before any field can be found.
Every sender has a layout
Every supplier sends its own invoice layout and changes it without notice. Extraction that depends on a fixed template per sender breaks the day one of them does.
Tables that span pages
A 300-line parts list or a long PO keeps going onto the next page, sometimes with the header repeated and sometimes without. The rows have to come back whole and in order.
Handwriting and markup
Production sheets, field logs and signed receivers carry handwritten values, crossed-out numbers and initials. Those need a person in the loop when the model is not sure.
Drawings are not documents
On a print, the value that matters is a callout next to a feature, with a tolerance and a note that chains to a customer standard. Reading it takes knowing what a callout is.
Four questions to ask any PDF extraction tool
- Run it on your own hardest documents, not the vendor's samples.
- Ask for accuracy per field, not per page. A page with one wrong price is a wrong invoice.
- Ask what happens when the model is unsure: does the document stop, or does a guess reach the ERP?
- Ask where the output goes. A JSON file still has to be mapped, checked and keyed into the ERP by someone.
Extraction Structify has shipped.
- Idaho Transportation Department
15,000 boring logs
Handwritten and digital logs, produced by different tools over decades, structured into one standard format the engineering team can search by location and date.
Read the ITD case study - Harney & Sons Fine Teas
20+ paper forms
Production ran on paper forms that were retyped into spreadsheets. They became validated digital capture, and inbound purchase orders are now read, classified and previewed for approval before anything is written to SAP.
Read the Harney & Sons case study - A precision CNC shop
$400K saved
Customer prints turned into control plans by one tested engine, in a two-week project.
Read the precision machining case study
An extraction tool, or extraction into the ERP.
Document extraction tools and APIs return fields. Structify returns records the ERP accepts. If you have developers who will build the checks, the review queue and the ERP integration themselves, a standalone tool is the right call. If you want the whole path built and owned by you, that is what Structify does.
| Standalone extraction tool | Structify | |
|---|---|---|
| What you get back | A file or an API response with the fields it found | A record in your ERP, checked and approved |
| How a field is checked | A confidence score for each field | Against the PO, the part master, your price tolerances and the receipt |
| What happens to exceptions | You build the review queue and the routing | A review queue with the reason, routed to the person who owns it |
| Who sets it up | Your team configures models and writes the integration | A forward-deployed engineer builds it with your team |
| Who owns it afterward | The vendor's models and your integration code | You own the code and the data warehouse |
Applications built on document extraction.
Each one is in the catalog and connects to the ERP you already run.
- RFQ IntakeReads inbound RFQs and turns them into structured quote requests.
- Quote to orderReads the request, drafts the quote, and turns the customer's PO into a sales order without retyping a line.
- PO ProcessingThree-way matches POs, receipts and invoices, and flags what will not reconcile.
- AP and AR reconciliationCollects invoices from the inbox, portals and scanned paper, and posts the ones inside your tolerances.
- Customer drawing to control planPulls every dimension, tolerance and critical characteristic off the print and builds the plan in your format.
Questions about AI data extraction
Ask us directlyGet a blueprint foryour AI transformation.
Book a demo