How Agentic AI is Transforming Logistics with Emeis Tech

Challenges

Formula2Ship had a bold mission:

To simplify logistics by offering the power of multiple courier partners through one intelligent platform—capable of dynamically selecting the best partner based on cost, performance, delivery time, and region.

However, as shipments scaled into the thousands per day, traditional rule-based automations began to break:

  • Rate APIs were slow or failed intermittently
  • Orders with special constraints (COD, temperature-sensitive, high priority) needed constant manual overrides
  • SLA violations were hard to predict or recover from in real-time
  • Logistics ops teams were overwhelmed by exception handling

The Emeis Solution: Agentic AI for Logistics Autonomy

Emeis Technologies stepped in—not just as a development partner, but as a deep-tech AI strategist.

We deployed our Agentic AI Framework into Formula2Ship to build autonomous decision-making and execution capabilities across key areas:

How Agentic AI Transformed Formula2Ship

    1. Smart Shipment Orchestration – Instead of static courier rules, we deployed autonomous agents that:
      • Assessed live rate APIs across providers
      • Balanced delivery SLAs, cost, RTO risks, and geographic history
      • Made shipment decisions in real-time—without human input
      • Smart Shipment Orchestration
    2. Proactive Exception Handling – Agents monitored:
      • API failures
      • SLA breaches
      • Undelivered shipments
      • And took action automatically: e.g. re-assigning shipments, notifying clients, or switching logistics partners with zero downtime.
    3. Autonomous Workflow Optimisation – Agents self-adjusted pickup batching, last-mile partner choices, and delivery timings to:
      • Reduce RTOs by 14%
      • Improve on-time delivery by 21%
      • Save ops team 60+ man-hours/week
  1. AI-Driven Customer Communication
    • Agents personalized communication (via WhatsApp/SMS) based on user behavior, delivery progress, and past interaction history—enhancing NPS and reducing support load.

Technical Highlights

  • LLM-powered agents with real-time retrieval + memory

  • Tool-using architecture: Courier APIs, tracking APIs, ERP connectors

  • Dynamic goal reprioritization under volatile conditions

  • Feedback loops to continuously learn from failed deliveries

Results

  • Metric Before After Agentic AI

  • Orders Processed/Day 5,000 22,000+

  • Ops Escalations/Week 110+ <25

  • RTO Rate 19% 13%

  • Average SLA Violation

  • Response Manual (Avg 4-6 hrs) Instant

  • Monthly Revenue Growth – 🚀 3.2x in 3 monthsv

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