Customer Success Story

AI-Powered Invoice Processing Automation for Global Logistics Provider

Kousik Rajendran

Jun 22, 2025

A leading logistics provider automated the processing of 100,000+ biweekly invoices from multiple carriers using an AI-powered, serverless AWS solution. The system ingests emails via Amazon SES, extracts and validates data with Amazon Textract and Bedrock, and processes Excel files with Lambda. This reduced manual labor costs by 70%, cut invoice processing costs by 40%, and decreased errors by 30%, delivering real-time financial visibility and enhanced compliance.

A leading logistics provider automated the processing of 100,000+ biweekly invoices from multiple carriers using an AI-powered, serverless AWS solution. The system ingests emails via Amazon SES, extracts and validates data with Amazon Textract and Bedrock, and processes Excel files with Lambda. This reduced manual labor costs by 70%, cut invoice processing costs by 40%, and decreased errors by 30%, delivering real-time financial visibility and enhanced compliance.

Customer Challenge

A leading logistics provider faced bottlenecks in scaling their business due to manual processing of 100,000+ invoices every two weeks from multiple carriers. These documents arrived in fragmented formats including PDF, TIFF, and JPG files, creating a complex data extraction challenge that required manual reviews. This labor-intensive process had evolved into an operational bottleneck, generating high error rates and inconsistent data quality.

Solution

We partnered with the customer to build an intelligent, AI-powered invoice processing system leveraging AWS-native services to create a scalable, event-driven architecture. The solution addressed the complex requirements of automated email and document processing using a fully serverless AWS stack.

Architecture

The solution leverages Amazon Simple Email Service (SES) for secure email ingestion, automatically depositing emails and attachments into Amazon S3 with event notifications to trigger downstream processing. Amazon Bedrock Claude Sonnet 3.7 model is used for advanced AI-powered classification and validation and Amazon Textract for PDF extraction and Lambda functions for Excel processing.

Key Outcomes

  • 70% reduction in manual labor costs through complete automation 

  • 40% decrease in invoice processing costs within the first quarter

  • 30% reduction in downstream errors and rework, directly improving cash flow

  • Real-time visibility into freight accrual calculations and financial operations

  • Enhanced compliance through standardized data capture and comprehensive audit trails