All case studies
Finance4 weeks

90% reduction in manual invoice processing time

A 25-person accounting firm was manually processing 500+ invoices per month across 40 clients. We built an AI extraction pipeline that reads, categorizes, and routes invoices automatically.

0%

less manual processing

0+

invoices per month

0 weeks

to production

The Challenge

Two full-time staff spent their days manually entering invoice data into QuickBooks. Error rates were 8%, and month-end close took 5 days because of reconciliation issues.

Our Approach

  1. 01

    Diagnosed: Shadowed the team for 2 days to map the full invoice lifecycle.

  2. 02

    Scoped: An OCR + LLM pipeline that extracts, validates, and routes invoice data.

  3. 03

    Built: Document processing with confidence scoring and human-in-the-loop for low-confidence extractions.

  4. 04

    Verified: Processed 200 historical invoices and compared against manual entries.

  5. 05

    Shipped: Deployed with a 2-week parallel run before cutting over.

The Outcome

Invoice processing went from 3 minutes per invoice to 18 seconds. Error rate dropped from 8% to 0.3%. Month-end close shortened from 5 days to 2.

My staff went from data entry to actual accounting work. That's what I hired them for.

Managing Partner

Regional accounting firm, 25 employees