# Affinda and Infor LN: AI document capture for invoices and orders > Source: https://netray.co/stack/affinda-document-capture-infor-ln > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: ERP Stack ## Short answer Affinda is a cloud AI document extraction service that lists Infor, with LN among the supported products, as an integration target. Its page does not document the exact LN mechanism, so treat the integration as something to scope with Affinda: typically extracted fields are returned as structured data and loaded into LN through your own mapping. If documents cannot leave your network, plan for that early. ## Erp Infor LN ## Erp Key infor-ln ## On Prem true ## Product Affinda document capture for Infor ## Vendor Affinda ## Category Document capture and OCR ## Integration **Method:** Extraction API plus a mapping layer you own **Detail:** Affinda's page lists Infor but does not detail the LN method. The general pattern for a capture service is: send the PDF or image, receive JSON fields (supplier, invoice number, dates, lines, totals), then post them to LN. In LN that post is usually done through ION and a BOD, a Business Interface, or a data import session, whichever your team already supports. **Method:** Review queue before posting **Detail:** Low-confidence fields should land in a human review step, not go straight into LN. Decide whether review happens in Affinda's tooling or in an internal screen, and keep the original document linked to the LN record for audit. ## Data Flows **From:** Supplier invoice (PDF, email) **To:** Affinda **Data:** Document image or PDF **Trigger:** Mailbox rule or upload **From:** Affinda **To:** Mapping layer **Data:** Extracted header and line fields with confidence scores **Trigger:** Extraction complete **From:** Infor LN **To:** Mapping layer **Data:** Open POs, suppliers, tax codes, currencies for matching **Trigger:** Lookup at validation time **From:** Mapping layer **To:** Infor LN **Data:** Validated invoice for posting or approval **Trigger:** Passes validation or reviewer approves **From:** Rejected documents **To:** AP clerk **Data:** Fields that failed match or confidence checks **Trigger:** Validation failure ## Setup ### Confirm the LN mechanism with Affinda **Detail:** Ask for the written method they support for your LN version, since the public page does not describe it. ### Decide data residency **Detail:** Check where Affinda processes and stores documents and whether that fits your contracts and any export-control rules. ### Define the document types **Detail:** Start with supplier invoices only. Add order confirmations or delivery notes later, each with its own extraction model. ### Build the supplier and PO lookup **Detail:** Match on LN business partner ID, tax number and PO number. Cache lookups so validation is fast. ### Choose the LN entry point **Detail:** Pick ION BOD, Business Interface or import session and test posting a single invoice in a non-production company. ### Set confidence thresholds **Detail:** Route anything under the threshold, or any new supplier layout, to human review. ### Run parallel for a cycle **Detail:** Process one month both manually and through capture, and compare totals and tax before cutting over. ## Pitfalls - Invoices from the same supplier with several layouts or languages lowering extraction accuracy until each is tested. - Tax codes and withholding handled differently in LN than on the document, so totals match but tax does not. - Duplicate postings when the same invoice arrives by email and by portal; use supplier plus invoice number as a key. - Line-level matching failing when the PO line was changed in LN after the supplier invoiced. - Currency and rounding differences between the document and the LN exchange rate on the posting date. - Confidential drawings or pricing in attachments leaving the network without anyone having decided that is acceptable. ## Ai Layer ### Exception triage **Description:** A private assistant reads rejected documents and the matching LN PO and receipt, then explains in plain language why each failed and what the clerk should check. ### Supplier layout drift **Description:** It compares recent extraction errors by supplier and flags layouts that changed, so templates can be retrained before AP backs up. ### Plain-language AP questions **Description:** Let AP ask which invoices are waiting on a receipt, with the underlying LN query shown, read-only. ### On-prem extraction option **Description:** Where documents must stay inside the network, an open-weight vision-language model served on your GPUs can handle extraction for the document types you select, with a human approving what posts to LN. ## Alternatives - Use an AP automation product with a documented LN connector if you want a supported path rather than a mapping layer you maintain. - Use EDI or supplier portal invoicing for your top suppliers, which avoids OCR errors entirely. - Keep manual entry if monthly invoice volume is low; capture only pays off with steady volume. ## Faq ### Does Affinda have a native Infor LN connector? **Answer:** Its integrations page lists Infor and names LN among the supported products, but it does not describe the mechanism. Ask Affinda for the specific method and the LN versions they have tested before you plan the project. ### Can document capture run fully on-prem? **Answer:** Affinda is a cloud service. If documents must stay inside your network, you would look at a self-hosted extraction approach instead, or confirm Affinda's deployment and residency options in writing. ### How does extracted data get into LN? **Answer:** Usually through ION and a BOD, a Business Interface, or an import session, driven by a mapping layer that validates against LN suppliers and POs first. Which one you choose depends on your LN version and what your team already supports. ### Should every invoice be auto-posted? **Answer:** No. Post automatically only when supplier, PO and amounts match within tolerance and confidence is high. Everything else should go to a person, and approvals should stay in LN's normal workflow. ## Source https://preview.affinda.com/integrations/infor ## Search terms affinda infor ln invoice capture, infor ln invoice OCR, infor ln accounts payable automation, affinda infor integration, infor ln document capture, ai invoice extraction infor ln --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json