AI Solutions for Streamlined Logistics and Seamless Data Integration

In the rapidly changing landscape of logistics, companies are constantly seeking innovative solutions to streamline operations and boost efficiency. DigiTrans develops a Digital Entry Automation (DEA) solution, designed specifically for logistics companies, transforming traditional manual data entry processes with advanced AI-powered document recognition.

Introducing DigiTrans

DigiTrans is an artificial intelligence partner for companies in logistics. They help companies to reduce manual tasks and increase their productivity. The company specialises in building AI solutions that drive innovation in the logistics sector. Our collaboration with Digitrans showcases our expertise in AI model development and MLOps. In this case, we demonstrate how our solution can improve document and data management, a critical aspect of the operations of logistics companies.

Navigating Document Complexity

The logistics industry is overwhelmed with various types of documents—generated PDFs, Excel files, scanned documents, orders in emails, etc. For DigiTrans’ customers, managing this influx efficiently is a significant challenge. Traditional document processing methods are labor-intensive, prone to errors, and struggle to keep pace with growing data flows. Hence, there was a need for a robust solution to accurately extract data and integrate it into logistics companies' systems.

Our team works closely with DigiTrans to develop an AI solution tailored to the logistics industry. By using advanced machine learning (ML) models and semantic AI, we created a system capable of extracting, classifying, and analyzing information from diverse document formats.

In practice, the end user forwards all documents to a data entry assistant via email. All messages received at this email address are automatically processed into a machine-readable file and sent to a preferred system, such as a transport management system or ERP.

Taking the Necessary Steps

• Understanding Customer Needs: Our team of data scientists and developers conducted an in-depth analysis of the challenges DigiTrans customers face, identifying key pain points to address.
• Examining Data Sources: An experienced data scientist on our team reviewed all data sources, standardizing the processing of PDFs, scanned documents, and emails to ensure consistency and reliability.
• Unifying NLP Model Input: We developed a tool to extract and standardize information from various document formats, enhancing data quality and converting PDFs into user-friendly formats.
• Organizing Document Labeling: We implemented a document labeling tool, enabling a dedicated team to efficiently label documents. Clear guidelines and quality assurance protocols were established to maintain accuracy.
• Training the NLP Model: Our NLP model is undergoing a structured three-step training process to accurately extract the necessary information for DigiTrans' forms.

Using Open Source Tools

To bring the solution to life, we use a range of open source tools:

• PyTorch for analysing, interpreting and classifying documents;
• Google Translate to provide accurate translations, addressing the need to process multilingual documents;
• Tesseract OCR for converting document images into machine-readable text, enhancing text recognition accuracy;
• Python as our development backbone, to develop the applications and the orchestration of the AI models;
• OpenCV for image pre-processing to improve document readability and precise text extraction;
• Nomad and Docker for the deployment of the applications and AI-Models.

Implementing AI into Production

• Increased Efficiency: Automated document processing significantly reduces manual data entry and errors;
• Scalability: The solution's microservices architecture, coupled with MLOps, allowed it to scale with the growing needs;
• Continuous Improvement: MLOps practices ensured continuous deployment and monitoring, keeping the system up-to-date with the latest advancements;
• Improved Data Accuracy: Advanced NLP and ML techniques provided precise text recognition and analysis, enhancing overall data quality and reliability.

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• Through this collaboration, we demonstrated how our expertise in AI model development and MLOps optimizes document and data management in logistics.
  

If the transformative process of DigiTrans, inspires you, and you're ready to lift your business or project to new levels with similar innovative outcomes, we encourage you to connect with us to explore possible solutions for you.