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AI Logistics Agent

Transforming Logistics with AI-driven Optimization

In today's dynamic supply chain landscape, logistics teams face mounting pressure to deliver faster, optimize costs, and respond to real-time disruptions. Manual planning and static rules are no longer sufficient. Our AI-powered Supply Chain Route & Fleet Optimizer leverages agentic workflows and machine learning to automate and enhance every step of logistics—from route planning to vehicle assignment and incident management—empowering organizations to achieve new levels of efficiency and resilience.

About the Solution

The AI-powered Supply Chain Route & Fleet Optimizer is a practical, enterprise-grade platform, product engineering, and design. Built as a realistic proof-of-concept (POC), it demonstrates how agent-based automation and machine learning can solve real-world logistics challenges for mid-sized firms.

How AI Powers the Solution

  • Agentic Workflows: Modular agents autonomously handle route optimization, vehicle recommendation, trip scheduling, and incident detection, collaborating to deliver end-to-end automation.
  • Machine Learning & Rule-based Logic: ML models and business rules are combined to select optimal routes, predict vehicle fitness, and simulate real-world disruptions.
  • Real-time Data Processing: The system ingests and reacts to live or simulated data (routes, weather, vehicle health, incidents) for dynamic decision-making.

Business Value

  • Maximize Fleet Utilization: Assign the best-fit vehicles and routes, reducing downtime and operational costs.
  • Proactive Incident Management: Detect and respond to disruptions in real time, minimizing delays and improving reliability.
  • Accelerate Decision-Making: Automate complex logistics workflows, freeing teams to focus on strategic tasks.
  • Showcase AI/ML Capabilities: Demonstrate Divami's ability to deliver practical, data-driven solutions to prospective clients.

Solution Workflow

  1. User requests a delivery: Specifies source and destination.
  2. Route Optimization Agent: Suggests the best route using ML and rule-based scoring (distance, time, weather, blockers).
  3. Vehicle Recommendation Agent: Selects the most suitable vehicle based on predictive maintenance and availability.
  4. Trip Scheduling Agent: Books the trip, assigns vehicle and route, and manages trip status.
  5. Incident Detection Agent: Monitors for incidents and triggers alerts or rerouting as needed.
  • Scalability: Automate planning for hundreds of vehicles and routes.
  • Adaptability: AI agents learn from data and adapt to changing conditions.
  • Integration: Easily connect with existing logistics, ERP, and analytics systems.
flowchart TD
    A[Customer Requests Delivery] --> B[AI Suggests Best Route]
    B --> C[AI Recommends Fit Vehicle]
    C --> D[Trip is Scheduled]
    D --> E[Trip Starts & Is Monitored in Real Time]
    E --> F{Incident or Delay Detected?}
    F -- No --> G[Trip Continues as Planned]
    F -- Yes --> H[AI Reroutes & Updates Plan Instantly]
    H --> I[Customer & Team Notified]
    G --> J{Destination Reached?}
    I --> J
    J -- No --> E
    J -- Yes --> K[Trip Completed & Status Updated]

Demo