All case studies

Small business, United States and United Kingdom

A Small Business Finance Team: Ending Manual Invoice Data Entry

A small business finance team replaced manual invoice entry with an AI pipeline that extracts, validates, routes and posts invoices to QuickBooks. Cycle time fell from five days to under one.

Timeline: Six-week deployment roadmap, including a pilot launch before full rollout

• 5 days to under 1 day Invoice cycle time
• 95%+ Accuracy, with 85% fewer errors
• $50,000 Annual saving from 40% less manual effort
• 100% Traceability of actions and approvals
• 1 FTE Freed (20% productivity increase)

The problem

The finance department received hundreds of invoices each month from multiple vendors and internal cost centres. Staff spent hours extracting invoice data, checking vendor details, chasing approvals and updating the ERP system by hand. Approval delays caused payment bottlenecks and strained vendor relationships, disconnected systems meant duplicate data entry, and manual work led to errors and compliance issues.

• Invoice data extracted by hand, slowly and with errors
• Approval delays strained vendor relationships
• Disconnected systems required duplicate data entry
• Data entry mistakes created compliance issues

What we built

We built an invoice pipeline in n8n. Invoices are captured from Outlook attachments and bulk-upload folders, and Gemini AI reads each one to extract header, line item and vendor details into Airtable. Business rules then validate the data, match it against existing purchase orders, and flag duplicates and exceptions. Approved categories route to the right department for multi-level approval across finance, operations and procurement, and approved invoices post automatically to QuickBooks with general ledger updates, real-time dashboards and a full audit trail.

Tools: Microsoft Outlook, n8n, Gemini AI, Airtable, QuickBooks

How we ran it

Every engagement follows The Claro Build Framework.

1. Assess: We traced each invoice from inbox to ERP and identified manual extraction, email-driven approvals and duplicate data entry as the main sources of delay and error.
2. Design: We designed the extraction fields, validation and purchase order matching rules, and a multi-level approval flow by department.
3. Build: We set up OCR extraction and the Airtable database, built the approval workflows, validation rules and QuickBooks integration, then ran a pilot before full rollout.
4. Sustain: The finance team was handed the system under The Adoption Standard: a structured 45-minute handover call and documentation written as it was built.

The result

The invoice cycle fell from five days to under one day. Accuracy reached more than 95 per cent, errors fell by 85 per cent, and every action and approval is now traceable. Manual effort dropped by 40 per cent, saving $50,000 a year and freeing one full-time role.

Client name withheld for confidentiality.