Automate Invoice Processing with a Custom AI System

Many businesses start with their accounting software's built-in tools, like QuickBooks Online's receipt capture. This feature works for simple, single-page receipts but fails on multi-page invoices with detailed line items. The OCR frequently misinterprets data, cannot reliably match invoices to purchase orders, and requires significant manual correction, defeating the purpose of automation.

Tools like Bill.com are a step up but impose a rigid, one-size-fits-all workflow. Their AI struggles with non-standard invoice layouts, forcing you to manually correct GL codes and vendor details. The per-invoice pricing model also penalizes businesses with a high volume of transactions, and you are locked into their ecosystem for payment processing, which may not suit your existing banking relationships.

Consider a 20-person B2B service firm that receives 300 vendor invoices a month. The operations manager spends over 10 hours monthly forwarding PDFs from an inbox, manually keying data into QBO, and chasing department heads for approvals via email. An invoice from a new contractor with a slightly different layout requires them to print it out and enter it by hand. This manual process is not just slow; it's how a critical payment gets missed, leading to a late fee and a damaged vendor relationship.

The structural problem is that off-the-shelf tools are designed for the median company. They cannot handle your specific business rules, like routing an IT invoice over $1,000 to the CTO for approval but only if it lacks a PO number. You are forced to adapt your business process to the software's limitations, rather than building a system that reflects how you actually operate.

The engagement starts with a discovery audit of your current accounts payable process. Syntora maps every step from an invoice arriving in your inbox to the moment it is paid and reconciled. We identify your 5-10 highest-volume invoice layouts and document your specific approval logic. This audit results in a clear process map and a fixed-scope proposal before any code is written.

The technical approach would use Python and FastAPI to build a service that monitors your designated AP inbox. When a new invoice PDF arrives, an AWS Lambda function is triggered. The Claude API performs OCR and structured data extraction, trained on examples of your specific invoice formats for high accuracy. All extracted data, including line items and PO numbers, is stored in a Supabase PostgreSQL database, creating a permanent, searchable archive.

The delivered system provides a simple web dashboard for your team to review, edit, and approve extracted invoice data. A one-click approval pushes a perfectly formatted bill or journal entry directly into your accounting software via its API. The system dashboard shows processing time per invoice (typically under 60 seconds), tracks accuracy rates targeting 98%+, and gives a real-time status of every invoice. You receive the full source code and a maintenance runbook.