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CASE STUDY: Logistics Enterprise

AI-Powered Operations Platform

Replacing thousands of manual hours with a custom LLM orchestration pipeline for document processing and routing.

OpenAI APIPythonNode.jsERP
98.5%AI Accuracy
14h/dayManual Hours Saved
6 WeeksROI Achieved In
8 minsProcessing Speed
01

The Challenge

Drowning in unstructured documents.

The logistics company was processing over 1,200 PDF shipping manifests daily. A team of operators spent 14 hours a day manually reading, translating, and typing the data into their legacy ERP system, resulting in high error rates and bottlenecks.

  • 14 hours of manual data entry daily.
  • High human error rate in critical customs data.
  • Inability to scale operations without hiring heavily.
02

The Approach

Intelligent document orchestration.

We built an event-driven Python pipeline utilizing Azure Document Intelligence for OCR and GPT-4 for semantic extraction. The system parses unstructured data, validates business logic, and syncs directly to the ERP via a secure Node.js middleware layer.

  • Serverless Python functions for image processing.
  • GPT-4 for intelligent field mapping and translation.
  • Node.js API gateway for secure ERP integration.
03

The Solution

From hours to seconds.

The automated pipeline now handles 98.5% of documents completely autonomously in under 8 minutes per batch. The operations team was reassigned to high-value exception handling, completely transforming the company's throughput and profitability.

  • 98.5% zero-touch autonomous processing.
  • Complete elimination of data entry bottlenecks.
  • Seamless multi-language translation.
MONOLITH API
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