From 40 Hours of Data Entry to Zero.
How a mid-sized logistics company eliminated manual invoice processing, saving $408,000 annually with a custom AI extraction pipeline.
The Manual Tax
The client's AP department was receiving over 2,000 PDF invoices per week from various vendors, each with a completely different layout. A team of three full-time clerks spent their entire week manually opening emails, downloading PDFs, finding the relevant line items, and typing them into their legacy ERP system.
This process was not only expensive but highly prone to human error, leading to delayed payments, vendor disputes, and a massive bottleneck as the company tried to scale operations.
The AI Intervention
We didn't try to replace their ERP or force vendors to use a standardized portal. Instead, we built an invisible AI layer that sits between their email inbox and their database.
Using a custom Vision-Language Model (VLM) pipeline, the system now automatically intercepts incoming emails, extracts the PDF, reads the unstructured data regardless of the invoice format, validates the totals, and pushes the structured JSON directly into the ERP via API.
Workflow Transformation
Under the Hood
Tech Stack
- 01 Ingestion Layer AWS SES + Lambda for email interception and attachment parsing.
- 02 Extraction Engine Anthropic Claude 3.5 Sonnet (Vision) for unstructured data extraction to strict JSON schema.
- 03 Validation Logic Python/Pydantic layer to verify line-item math matches totals before ERP injection.
- 04 Integration Custom REST API connector to legacy NetSuite instance.
Unit Economics
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