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Logistics & Supply ChainGlobal Freight Forwarder & 3PL Operator

Autonomous Freight Manifest & Customs Processing Pipeline

92%Reduction in manual manifest data entry time
<14sAverage document ingestion to TMS synchronization
99.4%Field extraction accuracy on degraded scans
The Business Problem

The client received over 1,400 daily multi-page Bills of Lading, packing slips, and customs declarations in erratic non-standard PDF scans. Over 22 full-time operations coordinators were required solely to manually type shipping details into the internal TMS, causing constant port clearance delays.

Technical Stack Deployed:
PythonFastAPIAWS TextractClaude 3.5 SonnetPostgreSQLDockerRabbitMQ
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Engineering Breakdown

Implementation Phases & Pipeline Architecture

PHASE 01 // Ingestion & De-noising

Automated email parsing and SFTP listener routing high-res multi-page PDF files into an asynchronous RabbitMQ queue.

PHASE 02 // Vision OCR & Layout Graphing

Custom vision pipeline identifying tabular line items, container numbers, and consignee signatures.

PHASE 03 // Validation & Anomaly Gate

Mathematical verification ensuring total weights and line item sums match invoice totals before posting.

PHASE 04 // TMS / EDI Synchronization

Direct dispatch into legacy systems with automated audit logging.

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