Ztronix
Manufacturing
India
DATADOVE engineered an AI-powered backend automation system for manufacturing operations focused on BOM extraction and raw material planning. Engineering teams previously depended on manual extraction of part numbers, quantities, and specifications from highly complex PDF drawings.
The organization handled large volumes of engineering documents daily, resulting in slow processing cycles, operational bottlenecks, and procurement delays. Teams lacked workflow visibility, and manual validation introduced frequent data inconsistencies and rework.
Using AWS Bedrock, Python, Node.js, and Amazon S3, DATADOVE automated PDF ingestion, AI-powered extraction, workflow orchestration, and procurement planning. The solution transformed unstructured engineering documents into structured operational intelligence.
Reduced BOM extraction time by nearly 80% across manufacturing workflows.
Enabled real-time workflow tracking and procurement planning transparency.
Built modular AI systems capable of handling enterprise-scale document processing.
Engineering PDFs, cable harness diagrams, and BOM sheets are securely uploaded and stored in Amazon S3 for automated processing workflows.
AWS Bedrock and Python-based AI models automatically extract BOM items, quantities, descriptions, and vendor references from unstructured engineering documents.
Internal teams can validate extracted data, edit workflows, and reprocess requirements without restarting the operational pipeline.
Structured BOM data flows into procurement planning systems where inventory checks, shortages, and vendor recommendations are automatically calculated.
The platform aggregates supplier pricing, stock availability, MOQ, and procurement insights to support operational decision-making.
Completed workflows are archived for reporting, operational visibility, and future manufacturing reference.
~80% reduction in manual BOM extraction time
Improved procurement planning efficiency
Real-time workflow visibility for teams
Higher operational accuracy and consistency
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