Swiss E-Commerce Team Cuts Invoice Cycle Time 47% with a Claude Extraction Pilot

Background: A Swiss E-Commerce Operations Team at the Pilot Stage

This case study is a composite drawn from patterns Forfis has observed across multiple engagements. We do not name real clients. The company described here is a plausible representative of a profile we have worked with repeatedly: a mid-sized Swiss e-commerce and retail operations firm, roughly 120 employees, running a mixed stack of SAP Business One for ERP, Microsoft Teams for internal communication, and a legacy document management system for incoming supplier invoices. The team was in the “running isolated pilots” stage of AI maturity: they had experimented with a generic OCR tool on a small sample of invoices, seen promising results, but had no structured process to move from experiment to production. The finance and operations leads wanted a repeatable path, not another one-off test.

Challenge: 1,800 Invoices a Month, No Headroom, and a Compliance Clock

The operations team processed roughly 1,800 supplier invoices per month across 14 business days. Each invoice required a clerk to open the PDF, transcribe vendor name, line items, tax codes, and payment terms into SAP Business One, then flag discrepancies for review. The average cycle time from receipt to ERP entry was 3.2 days, with a field-level error rate of 11% on a 200-invoice sample. Two pressures made the status quo untenable: first, the EU AI Act’s transparency and human-oversight obligations (Articles 13 and 14) meant that any automated system handling financial data needed a documented approval workflow, and the team had no such process in place. Second, the operations lead was managing a 20% volume increase tied to a new retail distribution agreement that closed in six weeks. Hiring two additional clerks would have cost roughly CHF 14,000 per month in fully loaded salary, and the onboarding cycle for a new finance clerk in the Swiss market was 4 to 6 weeks.

Approach: A Two-Week Pilot on One Workflow, Built on Claude and Teams

Forfis scoped a two-week, fixed-scope pilot on a single workflow: supplier invoice extraction and ERP entry. The architecture used the Anthropic Claude API for extraction, chosen for its 200K-token context window, which handled multi-page invoices and attached purchase orders in a single inference call without chunking. The model output was constrained to a JSON schema matching SAP Business One’s field structure. The integration path was deliberately thin: incoming invoices arrived via email to a monitored mailbox, a lightweight ingestion service pulled the PDFs, the Claude API extracted and classified the fields, and the result was pushed to SAP via its REST API. Approval requests and status updates routed through Microsoft Teams, where the finance team reviewed extractions above a CHF 5,000 threshold. The human-in-the-loop rule was explicit: any invoice touching a payment, a contract clause, or a tax code required a named approver’s sign-off before the ERP write. The pilot team included one Forfis engineer, one product designer, and the client’s operations lead, working as a dedicated AI team embedded in the client’s daily standup.

Outcome: 47% Faster Cycle Time, 5.8% Error Rate, Zero Re-Keys

The pilot ran for 10 business days on a live subset of 320 invoices. The measured results, compared against the pre-pilot baseline: cycle time from receipt to ERP entry dropped from 3.2 days to 1.7 days, a 47% reduction. The field-level error rate fell from 11% to 5.8% on the same 200-invoice verification sample. The finance team approved 94% of extractions without correction; the remaining 6% were flagged by the model’s own confidence score and routed to a human reviewer before ERP entry. No invoice required a full re-key. The operations lead reported that the two clerks who had been doing manual entry were redeployed to handle the 20% volume increase from the new distribution agreement without additional hiring. The pilot’s measured baseline and post-pilot metrics were delivered as a one-page report, which the client used in a board presentation to justify a rollout to the remaining 12 invoice workflows. The EU AI Act compliance documentation, including the human-oversight log and transparency disclosures, was included as an appendix.

Lessons for Teams Running Isolated Pilots

• Scope the pilot to one workflow, not one document type. The client initially wanted to pilot invoices, credit notes, and purchase orders simultaneously. Forfis pushed back: a single workflow with a full integration chain (ingestion, extraction, approval, ERP write-back, Teams notification) produces operationally meaningful metrics. A multi-document pilot with a partial integration chain produces vanity numbers. The client agreed, and the focused scope is why the two-week timeline held.
• The baseline is a contractual deliverable, not an afterthought. Without the pre-automation measurement of cycle time and error rate, the team cannot quantify the improvement or justify the rollout. Forfis builds the baseline measurement into the first week of the pilot, even if it means the automation work starts on day four instead of day one.
• Human-in-the-loop thresholds should be configurable, not hardcoded. The CHF 5,000 approval threshold was a starting point. During the pilot, the team observed that the model’s confidence score was a better predictor of error than the invoice amount. The threshold was adjusted to a hybrid rule: amount above CHF 5,000 OR confidence below 0.92 triggers human review. This reduced unnecessary approvals by 18% without increasing the error rate.
• Integration through existing APIs keeps the operational surface small. The client did not want a new front-end. The approval workflow lived in Microsoft Teams, the ERP write went through SAP’s REST API, and the ingestion service was a 200-line Python script. The total new infrastructure was one container and one API key. This kept the post-pilot operational overhead low and made the managed-operation retainer straightforward.
• EU AI Act compliance is a design constraint, not a documentation afterthought. The human-oversight log, the transparency disclosure to affected parties, and the model-output audit trail were built into the workflow from day one. Retrofitting compliance documentation after the pilot is live is more expensive and less defensible than building it in.