Customer Background

The client is a leading global logistics provider with experience of more than two decades in the transportation sector. They have a large customer base of over 50k individuals across more than ten countries. They manage a vast network of carriers, warehouses, and distribution centers. Their core services include shipment transportation, warehousing, and supply chain management.

  • Industry

    Logistics and supply chain management

  • Technologies / Platforms / Frameworks

    Artificial intelligence (AI), large language models (LLMs), MySQL

Challenges

The logistic company accumulated a large amount of data every day. It became challenging for their workforce to handle the data efficiently with manual processes. Their internal data is distributed across numerous digital and physical repositories. They did not have a centralized retrieval system. The information retrieval procedures were substantially inefficient. Their employees spent long hours to figure how to navigate different storage systems and locations.

The company faced several challenges, such as:

  • Manual booking process: The company relied on phone calls, emails, and spreadsheets for freight booking. This process was slow, lacked real-time visibility, and often led to miscommunication.
  • Inefficient communication: Coordinating with carriers, shippers, and consignees involves multiple stakeholders. Misunderstandings, delays, and missed opportunities were usual.
  • Contextual understanding: Extracting relevant information from unstructured text was difficult. Conventional systems struggled to realize the context.

Solutions

Our team of experts had thorough discussions with the client’s operations teams. We examined the challenges that they faced and realized the need to unify and centralize the company’s knowledge management platform.

The client’s processes needed advanced search capabilities, contextual understanding, and seamless integration with existing tools. Hence, our experts decided to integrate artificial intelligence. We built LLM-powered chat bot application, integrated AI-native search functionalities, and integrated MySQL for data extraction.

Automated booking system

  • Developed an AI-powered chatbot for shipment booking.
  • Customers and shipping agents interact with the chatbot via natural language.
  • The AI recognizes context, confirms availability, and approves bookings.

Result: Minimized booking time by 50%, improved accuracy, and enhanced customer experience.

Real-time communication

  • Integrated LLMs into the communication platform.
  • LLMs analyze clients’ messages, extract details, and provide proper responses.
  • Real-time translation expertise enables global communication.

Result: Quicker response times, reduced errors, and streamlined communication.

Document processing and compliance

  • LLMs process consignment-related documents faster.
  • Extract relevant information in no time.
  • Highlight inconsistencies or missing data for manual assessment.

Result: Reduced manual effort, improved accuracy, and better compliance.

Benefits

Efficiency boost

  • Minimized the time taken for booking process.
  • Faster response times increased facility utilization.
  • Improved resource allocation and load planning.

Cost-effectiveness

  • Lowered administrative overhead.
  • Reduced errors in bookings and documentation.
  • Decreased dispute resolution costs.

Improved customer satisfaction

  • Real-time updates and proactive communication.
  • Accurate documentation and timely delivery.
  • Enhanced customer loyalty and repeat sales.

Diagram

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