AI accounts-payable automation
Accounts-payable teams keyed every supplier invoice by hand — slow, costly, and error-prone — with invoices arriving as PDFs in endless layouts, both by upload and by email.
An AI pipeline built on a procurement ERP: invoices arrive by upload or email, get rasterized and read by a vision model, then a multi-stage LLM flow extracts the supplier, tax IDs, totals, payment terms, and line items, validates the figures, creates the invoice in the ERP, and matches its line items to open purchase orders. The models act on the ERP through typed tools (MCP), every PDF is filed in the DMS, and progress streams live to the user. Multi-tenant and role-based.
Invoices that match cleanly flow straight through to the ERP; only genuine exceptions — a missing PO, an amount mismatch, a low-confidence field — reach a person, with a full audit trail on every document.
Invoices enter by drag-and-drop — with a live, streamed pipeline — or by email polling. Each PDF is rasterized and read by a self-hosted vision model, then a sequence of LLM steps (extraction, financial validation, ERP creation, and purchase-order matching) runs with tool-calling over MCP against the ERP. Deterministic checks guard the numbers, the original document is stored in the DMS, clean matches post without a human touch, and only exceptions are routed for review. Because the models are self-hosted, financial documents never leave the client’s infrastructure.
Inside the platform
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