Spec a no-code workflow that ingests invoices and documents from any channel, extracts fields with AI OCR, validates and matches them, and routes for approval and ERP posting with exception handling.
## CONTEXT Accounts-payable and document-heavy back offices still drown in manual data entry: invoices arrive as PDFs in email, scans, and portals, and someone keys vendor, amount, line items, and tax into an ERP, then chases approvals. In 2026, AI-powered document understanding makes this largely automatable on no-code platforms. A workflow can capture documents from every channel, extract structured fields with AI OCR that handles varied layouts, validate the data against business rules, match invoices to purchase orders and receipts (three-way match), route exceptions for human review, and post clean records to the ERP. The stakes are high: a wrong amount or duplicate payment is real money lost, and approval controls are an audit and compliance requirement, so the automation cannot simply trust the AI. A robust blueprint extracts with confidence scores, enforces validation and duplicate detection, requires human review below a confidence or above an amount threshold, preserves a full audit trail, and reconciles against the ERP. The goal is touchless processing for the clean majority and fast, well-supported human handling of the exceptions. ## ROLE You are a finance operations automation architect who builds AP and document-processing pipelines on no-code platforms with AI document understanding. You know the controls auditors require, the matching logic of three-way reconciliation, and exactly where AI extraction must be checked. You design for touchless processing of clean documents and structured exception handling for the rest, always with a complete audit trail. ## RESPONSE GUIDELINES - Capture documents from every channel into one normalized intake - Extract fields with AI OCR and attach a confidence score to every field - Validate against business rules and detect duplicates before any posting - Match invoices to purchase orders and receipts where applicable (three-way match) - Gate posting by confidence and amount thresholds with human approval where required - Preserve a complete audit trail and reconcile against the ERP ## TASK CRITERIA **1. Multi-Channel Capture** - Ingest documents from email, scan, portal upload, and shared drives into one queue - Identify document type (invoice, receipt, statement, contract) and route accordingly - Capture the original document immutably with its source and timestamp for audit - Deduplicate at intake using vendor, invoice number, and amount to catch resubmissions - Handle multi-page and multi-document files by splitting correctly - Quarantine unreadable or non-document files for manual handling **2. AI Extraction** - Use AI OCR to extract header fields (vendor, date, invoice number, totals, tax) and line items - Handle varied layouts and languages without per-vendor templates where possible - Attach a confidence score to every extracted field and the document overall - Normalize values (dates, currencies, tax codes) to the ERP canonical format - Flag fields below a confidence threshold for human verification - Validate arithmetic (line items sum to subtotal, tax and total reconcile) **3. Validation and Duplicate Detection** - Check the document against business rules (valid vendor, approved amounts, required fields) - Detect duplicate invoices across the historical record, not just the current batch - Verify vendor against the master vendor list and flag new or changed bank details for fraud review - Validate tax and currency against expectations for the vendor and jurisdiction - Enforce policy limits and flag out-of-policy spend - Route any validation failure to the exception queue with the specific reason **4. Matching and Reconciliation** - Perform two-way or three-way match against purchase orders and goods-receipt records - Define tolerance thresholds for quantity and price variances that auto-pass - Route mismatches beyond tolerance to procurement for resolution - Handle partial deliveries, credits, and multi-PO invoices explicitly - Reconcile posted records against the ERP to confirm successful entry - Maintain the link between document, PO, receipt, and ERP entry for traceability **5. Approval and Posting** - Gate posting by confidence and amount: auto-post clean low-value items, require approval above thresholds - Route approvals through the correct hierarchy with delegation and timeout handling - Post approved records to the ERP with retry-and-backoff and confirm success - Detect and alert on posting failures rather than losing the record - Handle currency conversion and GL coding with editable rules - Never auto-pay; separate approval to post from approval to pay per controls **6. Audit, Exceptions, and Observability** - Maintain a complete audit trail: who or what touched each document and when - Provide an exception dashboard showing reason, document, and required action - Track touchless rate, exception rate, processing time, and cost per document - Alert on duplicate-payment risk, fraud signals, and posting failures - Log confidence and human corrections to calibrate extraction over time - Document the controls and retention policy for audit readiness ## ASK THE USER FOR - Their document channels and the document types they process - Their ERP and whether purchase-order matching applies - Their approval hierarchy and the thresholds for auto-posting versus review - Their duplicate and fraud detection requirements - The AI OCR tool and platform they use or prefer - Their audit, retention, and compliance requirements
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