Project Name
Intelligent Document Processing System for Supply Chain Operations
A leading retail and supply chain enterprise processed thousands of shipment-related documents every month, including delivery challans, packing slips, transport invoices, weighbridge receipts, and handwritten acknowledgements from logistics partners. These documents arrived in inconsistent formats, varied across vendors and regions, and frequently contained handwritten entries or unclear scans.
Operations teams manually reviewed each document, matched values with purchase orders, and validated vendor and shipment details. During seasonal demand spikes, backlogs created delayed inward processing and reduced warehouse throughput. The organization required a scalable AI-driven system that could automatically read, classify, extract, validate, and route incoming documents without relying on rigid templates.
Ksolves implemented an end-to-end AI document automation pipeline capable of handling high-volume and unstructured logistics documents with precision.
The challenges faced by the client are as follows:
- Heavy Document Variability: The client struggled with significant document variability due to widely varying formats across vendors, shipment types, and regions, making static templates unreliable for extraction.
- Handwritten Entries and Low-Quality Scans: Many documents, especially weighbridge slips and handwritten acknowledgements, contained handwritten notes or low-resolution scans, which reduced readability and caused frequent extraction errors.
- Time-Consuming PO Matching: The purchase order matching process became slow and effort-intensive, as teams had to manually verify quantities, vendor codes, dates, and shipment IDs for every incoming document.
- Seasonal Backlogs: During seasonal spikes in shipment volume, the client faced substantial processing backlogs that delayed operations and increased reliance on additional manpower.
- High Error Probability: The manual data entry workflow increased the likelihood of errors, often leading to discrepancies between delivered quantities and the values recorded in the system.
- Lack of End-to-End Digital Flow: The absence of an automated digital workflow created inefficiencies, as extracted data did not seamlessly sync with the ERP system, resulting in downstream inconsistencies.
The solutions provided by Ksolves are as follows:
- Unified Document Intake Pipeline: A centralized system to ingest PDFs, scanned images, and email attachments, automatically classifying each document type for correct processing routes.
- AI-Based Smart Extraction Models: Advanced OCR, NLP, and computer vision models capable of reading handwritten entries, extracting shipment details, identifying mismatches, and detecting signatures or stamps across irregular layouts.
- Automated Cross-Verification Engine: A hybrid rule-and-AI layer validating extracted fields such as quantities, vendor codes, shipment IDs, dates, and transport charges against internal records, flagging only exceptions.
- Reviewer-Friendly Feedback Console: A minimal interface allowing operations teams to review flagged entries, correct inaccuracies, and feed improvements back into the learning pipeline.
- ERP Integration Layer: Seamless conversion of validated records into ERP-compatible formats, ensuring automated data entry, complete audit logs, and consistent downstream operations.
- Unified Document Intake Pipeline: A centralized system for ingesting PDFs, scanned images, and email attachments reduced manual document sorting by 2x through automated classification and routing.
- Smooth Seasonal Scalability: The AI engine handled volume spikes without additional staffing.
- Fewer Quantity and Vendor Mismatches: Automated validations improved data accuracy significantly.
- Better ERP Data Quality: Clean, validated information reduced downstream adjustments.
- Improved Supplier Performance Insights: Document accuracy metrics provided actionable visibility.
By deploying a fully automated, AI-driven document processing workflow, we at Ksolves, through our advanced AI/ML services, enabled the retail supply-chain enterprise to accelerate shipment verification, improve data consistency, and eliminate manual bottlenecks. The scalable framework now supports expansion into additional document categories, including QC reports, gate passes, warehouse checklists, and freight bills.
Transform Your Supply Chain with AI-Driven Document Intelligence.
Partner with Ksolves to Automate, Optimize, and Scale Your Logistics Workflows.
