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Case Study

Automating Data Processing & Reporting for a Leading Logistics Provider

Client Overview

A leading logistics provider handling large volumes of shipment and billing data faced challenges in processing, storing, and sharing structured (XML) and unstructured (Base64) data. The existing manual approach led to delays, errors, and compliance risks, affecting overall operational efficiency.

Challenges

  1. Manual File Processing Delays – Each input file, containing XML and Base64 data, required manual extraction, validation, and processing, slowing down operations.
  2. High Risk of Data Errors – The manual separation of XML and Base64 components led to data inconsistencies and incomplete SQL database updates.
  3. Time-Consuming Document Conversion – Base64 data had to be manually converted into PDFs, delaying document availability.
  4. Lack of Automated Reporting & Notifications – Clients lacked real-time visibility into processed data, leading to communication inefficiencies.

Solutions : Intelligent RPA for Data Processing & Reporting

To eliminate inefficiencies, RESOLVENT deployed a custom RPA solution to fully automate the process. The bot performed:

  1. Secure SFTP File Transfer – Established an SFTP connection to retrieve input files in .txt format, ensuring a secure and efficient data transfer process.
  2. Automated Data Separation & Validation – Extracted XML and Base64 data based on predefined validation rules, reducing manual intervention and errors.
  3. Structured Data Processing & Storage – Generated Excel files for XML data and updated records in the SQL database for real-time accessibility.
  4. Base64 to PDF Conversion Using Python – The bot automatically converted Base64 data into PDFs, eliminating manual processing delays.
  5. Automated Reporting & Notifications – For each run:
  • The bot emailed structured Excel files and PDF documents to the client.
  • A consolidated report summarizing all processed files was sent at the end of each cycle, ensuring transparency and compliance.

Results & Impact

  • 65% Faster Data Processing – Automated file retrieval, validation, and processing reduced turnaround time from hours to minutes.
  • 98% Data Accuracy Eliminated human errors in file separation, SQL database updates, and PDF generation.
  • 30% Reduction in Operational Costs Reduced manual intervention enabled cost savings and better resource allocation.
  • Improved Data Security & Compliance – Secure SFTP-based file transfers and automated tracking ensured regulatory adherence.
  • Enhanced Client Experience & Transparency – Real-time email reports improved communication and decision-making.

Conclusion

By deploying AI-driven RPA automation, the logistics provider successfully transformed its data processing workflow, ensuring fast, accurate, and secure file handling. The automation led to significant cost savings, improved compliance, and enhanced operational efficiency, making data management seamless and error-free.