RayzentLabs
ai solutions

Document automation: from PDFs, photos and scans to clean records

Supplier invoices arrive as PDFs, WhatsApp photos and email attachments in a dozen layouts. Document automation reads them, matches them to purchase orders, flags mismatches and posts clean records to accounting — with a person reviewing only the ones the model is unsure about.

The problem it solves

Manual data entry costs a full-time salary per few hundred documents a month, introduces errors that surface at audit, and delays payments and reporting. Template-based OCR breaks the moment a supplier changes their layout.

how it works

From your data to a feature people rely on.

  1. Ingest from email, uploads, a shared drive or a WhatsApp inbox
  2. Vision-capable models extract line items with a confidence score per field
  3. Records above threshold post automatically; the rest land in a review queue showing the source region beside each field
  4. Two-way sync with accounting or ERP, and thresholds tuned monthly from your team's corrections
document extractiontriagewebhooksapproval flows
in practice

What it looks like in three businesses.

Accounts payable

Supplier invoices matched to purchase orders with tolerance rules; ~90% posted untouched after tuning.

Onboarding forms

KYC and admission forms read into the CRM, with ID fields masked and duplicates caught by similarity.

Call transcripts

Sales calls transcribed and turned into CRM notes, tasks and follow-up drafts for approval.

questions

Document automation: what people ask.

Does it work with handwritten or photographed documents?

Photographed and scanned documents, yes — vision models handle mixed layouts well. Handwriting is evaluated per case; the pilot on your own documents gives you the real accuracy number.

Which accounting systems can it post to?

Tally, Zoho Books, QuickBooks, SAP Business One and most custom ERPs through their APIs or import formats. We confirm during discovery.

All questions

See document automation working on your data.

A 30-minute demo on your own use case: what we would build, how long it would take with AI in the loop, and what it would cost. No deck, no obligation.