Document intelligence

Messy PDFs become
fields you can trust.

Invoices, receipts, and freight bills — extracted with layout + Groq, then reviewed before anything hits the warehouse.

INV-10482.pdf Needs review
VendorHarbor Freight Lines
Invoice date18 Aug 2026
Total$4,280.00
PO numberHover the field — the scan lights up

1-click interactive demo

Three documents. No file upload.

Sample cards are canned walkthroughs. Upload a text-layer PDF in Inbox to see real page boxes from PyMuPDF.

Sample UI

Invoice walkthrough

Hardcoded boxes on a demo invoice — not live spatial extraction.

Sample UI

Receipt walkthrough

Canned fields and boxes so you can click around without uploading.

Sample UI

Freight bill walkthrough

Multi-page sample layout. Live multi-page PDFs use Previous / Next on Review.

How teams use it

Upload a PDF. Fieldline renders the page, Groq fills fields, you approve exceptions, then JSON / CSV leaves the building.

  1. Ingest Upload PDFs from Inbox.
  2. Extract Fields, line items, dates, totals.
  3. Review Humans fix only what looks uncertain.
  4. Export JSON, CSV, SQL, webhook.

Human in the loop

Accuracy is a process, not a promise.

Layouts change. Scans smear. Tables break. Fieldline flags weak fields so your team confirms them — then the rest flows through.

Talk through a demo

Architecture

What you are buying under the UI

  1. IngestPDF upload
  2. DjangoWorkspace + APIs
  3. CeleryWorker queue
  4. PyMuPDFPage image + word boxes
  5. GroqStructured JSON
  6. ReviewAlign, edit, export

Destination integration grid — coming soon except JSON / CSV / webhook