
Project overview
About the project
Riverstone Group runs a portfolio of restaurants, cafes, and bars across Auckland, receiving thousands of supplier invoices a month on paper, PDF, and email. Their accounts team was manually typing every bill into Xero and chasing credit notes by hand. We built a document-intelligence pipeline that reads each invoice with OCR, extracts line items, matches them against purchase orders and delivery dockets, posts the bill into Xero, and reconciles supplier credit notes automatically — flagging only genuine exceptions for a human. Month-end stopped being a bottleneck.
The challenge
With 11 venues, Riverstone's two-person accounts team was drowning in 3,000+ supplier invoices a month. Each bill was hand-keyed into Xero, GST and GL codes were guessed under time pressure, and credit notes for returned or spoiled stock were routinely missed — money quietly left on the table. Month-end took a week and errors only surfaced at review. Generic receipt-scanning apps could read a total but could not match line items to orders or handle credit notes across venues.
Our approach
How we delivered
Document Modelling
Collected a sample of every supplier invoice and credit-note layout and tuned extraction to reliably read line items, GST, and references.
Matching Engine
Built three-way matching against purchase orders and delivery dockets, with price-variance and duplicate detection to catch errors automatically.
Xero Posting
Automated coding and straight-through posting of bills into Xero per venue, plus automatic reconciliation of supplier credit notes.
Exception Workflow
Delivered a review queue showing the original document beside extracted data, so staff only touch the small percentage that truly needs judgement.
What we built
Features delivered
Technologies
Tech stack used
More work
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