AI invoice processing that reads every supplier invoice, proposes the GL code, matches it to the PO and goods receipt, and blocks duplicates before payment. Your AP team works only the exceptions, with the evidence already attached.
AI invoice processing is the use of document AI and machine learning to capture supplier invoices from email, portals and scans, extract header and line data, assign GL codes and cost centres, and match each line to purchase orders and receipts. It outputs a posted, approval-ready bill in your ERP, or a routed exception that explains exactly which field, price or quantity failed and why.
The work is not hard. It is repetitive, spread across inboxes and approvers, and easy to get slightly wrong: a reissued invoice number, a second copy to another approver, a changed bank account. That is how duplicates and fraud get paid.
Average time to process one invoice across AP teams in Ardent Partners' 2025 benchmark.[1]
Average cost per invoice versus $2.78 for best-in-class teams in the same Ardent Partners study.[1]
of US organisations were hit by business email compromise in 2025, per the AFP Payments Fraud and Control Survey. Fake invoices and changed bank details arrive through the AP inbox.[2]
A typical occupational fraud runs about a year before it is detected, across 1,921 cases in the ACFE 2024 Report to the Nations. Billing and invoice schemes hide in routine AP volume.[3]
Reads PDFs, images, e-invoices and multi-page statements in any layout, with no templates to maintain per vendor.
Learns coding from your posted history and matches each line to the PO and goods receipt using your tolerances.
Checks every invoice against paid and open bills, and flags bank detail changes before the payment run.
We pick one metric, usually touchless rate or cost per invoice, baseline it from last quarter, and connect the AP mailbox and ERP read access.
Extraction and coding are tuned on a sample of your posted invoices. Your AP lead reviews every field the model gets wrong.
The system processes live invoices beside your team, then starts posting draft bills for approval. Exceptions go to named owners.
We report the metric against baseline, with error logs. You decide whether to move to Run, extend, or stop.
| Criterion | Manual process | Off-the-shelf tool | Stratgik build + run |
|---|---|---|---|
| Setup time | None | Weeks, fast for standard ERPs | 21-day pilot on live invoices |
| Line-item GL coding | Clerk judgement | Rules or basic suggestions | Learned from your posting history, reasons shown |
| Matching tolerances | Informal | Configurable within product limits | Set per vendor, category and entity |
| Duplicate and bank-change checks | Spot checks | Often included, varies by vendor | Across all entities and paid history |
| Custom ERPs and odd formats | Handled by people | Can be limited | Built to your systems |
| Best fit | Under a few hundred invoices a month | Standard processes on a supported ERP | Multi-entity, high-volume or complex matching |
Benchmarks show most AP teams still touch most invoices. The leaders do not have more staff. They have fewer exceptions and fewer manual steps.
Move the sliders to your volumes. The touchless share is an assumption until we measure it on your invoices during the pilot.
Illustrative estimate using your inputs and stated assumptions, not a quote or guarantee. The pilot measures the real figure against your baseline.
21-day production pilot on live invoices, one entity
per month, up to 5,000 invoices
per month, multi-entity and higher volume
Usage (model tokens, OCR pages, cloud hosting) billed at cost with no markup; deployed in your cloud account where required; taxes excluded. GBP and AED prices are indicative conversions from USD.
AI invoice processing typically reaches high field-level accuracy on clean digital invoices, but the number that matters is accuracy on your own supplier mix. We measure it during the pilot on your live invoices, field by field, and report it with the error log. Low-confidence fields never post silently; they route to a person for review, so accuracy gaps show up as exceptions, not wrong payments.
Our AI invoice processing starts with a fixed 12,000 USD, 21-day production pilot on your live invoices. If it hits the agreed metric, a Run plan from about 3,000 USD a month covers monitoring, retraining and support for up to 5,000 invoices. Model, OCR and cloud usage is billed at cost. Larger multi-entity rollouts are priced from 8,000 USD a month.
For varied supplier invoices, yes. RPA follows fixed screen steps and templates, so it breaks when a vendor changes layout or sends a scan. AI reads the document's meaning, extracts line items, and learns coding from history. RPA still works well for the final posting step into older ERPs, and we often use both: AI decides, a bot or API posts.
Yes. We post draft bills and read purchase orders, receipts and vendor masters through the standard APIs for NetSuite, SAP S/4HANA and ECC, Microsoft Dynamics 365, Sage Intacct and Xero. For custom or older ERPs we use a database connector or a file-based import. Nothing is posted as final without your approval rules being applied.
Duplicate payment detection compares each new invoice against open and paid bills using fuzzy matching on vendor, invoice number, amount, date and line content. It catches near-duplicates, such as a reissued number with an extra character, the same bill under two vendor records, or a copy sent to a second approver. Suspected duplicates are held before the payment run with both documents side by side.
A working production pilot takes 21 days: connection in the first three days, training on your posted history in week two, and live shadow processing in week three. A full rollout across entities usually follows over one to three months, depending on how many ERPs, currencies and approval chains are involved. Your AP team stays in control throughout.
A 30-minute call to agree the metric, then a fixed-price 21-day pilot on your live AP inbox.