AI-Driven Load Creation for a U.S.-Based 3PL Company

Client Overview

Industry: Third-Party Logistics (3PL)
Location: United States
Operations: International freight management with multiple carrier partnerships

Business Challenge

The client faced several operational challenges:

  • Time-Consuming Load Creation: Manually creating loads took 10–15 minutes per entry, leading to inefficiencies.
  • Diverse Data Inputs: Receiving load information from various customers in multiple formats, including emails, spreadsheets, and manual entries.
  • Error-Prone Processes: Manual data entry increased the risk of errors, affecting delivery schedules and customer satisfaction.
Our Solution

Our Chennai-based software development company engineered a robust, scalable solution encompassing:

1. Client Portal for Self-Service Load Creation
  • User-Friendly Interface: Developed a secure, intuitive portal allowing clients to create and manage loads directly.
  • Real-Time Validation: Implemented checks to ensure data accuracy, reducing errors and omissions.
2. AI-Powered Email Bot
  • Automated Email Parsing: Designed an AI bot to read structured emails sent to a designated address, extracting necessary load information.
  • Interactive Communication: If essential details are missing, the bot automatically replies, requesting the required information to complete the load creation process.
3. Conversational AI Chatbot
  • Natural Language Processing: Built a chatbot capable of understanding and processing load creation requests through conversational interactions.
  • Multi-Channel Support: Integrated the chatbot across various platforms, including web and mobile applications, ensuring accessibility for clients.
Results Achieved
  • Reduced Load Creation Time: Decreased from 10–15 minutes to 2–3 minutes per load.
  • Enhanced Accuracy: Minimized manual errors through automated data validation and AI-driven processes.
  • Improved Client Satisfaction: Offered multiple convenient channels for load creation, catering to diverse client preferences.
Technologies Utilized
  • Backend: Java
  • Frontend: Angular
  • Database: MySQL, Mongo
  • AI & Automation: Natural Language Processing (NLP), Machine Learning (ML), Robotic Process Automation (RPA)
  • Deployment: AWS Cloud Services
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