An AI agent pipeline reads incoming invoices, extracts structured data with OCR and LLMs, runs 3-way matching against purchase orders and receipts, and routes exceptions for approval — so your finance team only touches what actually needs a human.
An AI orchestrator routes each invoice through extraction, validation, and matching — applying business rules with a guardrails layer on top.
Invoices arrive via email, SFTP, or manual upload, with automatic deduplication.
OCR plus LLM extraction pulls vendor, amounts, line items, PO number, and tax — with confidence scoring.
A 3-way matching engine reconciles invoice, purchase order, and goods receipt within configurable tolerances.
High-confidence matches auto-approve; exceptions route to the right approver automatically.
Every step a finance team already does — automated, with a human still in the loop where it matters.
Email, SFTP, and manual upload, with duplicate detection before an invoice ever enters the pipeline.
Document Intelligence OCR combined with structured LLM extraction, flagging low-confidence reads for review.
Automatic reconciliation of invoice, PO, and goods receipt, with exception classification when things don't line up.
A reasoning orchestrator coordinates extraction, validation, matching, and routing agents, adapting the path per invoice.
A dedicated safety layer can override unsafe or low-confidence AI decisions before they reach approval.
A dashboard for exception handling, plus an AI chat assistant for AP analysts working the queue.
| Step | Manual (outsourced) process | With AP Automation |
|---|---|---|
| Cycle time per invoice | 15–30 minutes | Under 2 minutes (target) |
| Data entry | Manual keying into Oracle Financials | Automatic structured extraction |
| PO matching | Manual lookup and comparison | Automated 3-way match with tolerances |
| Exceptions | Queued for manual review with no prioritization | Auto-classified and routed to the right approver |
We're looking for finance teams to pilot AP Automation on real invoice volume.
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