Agentic AI-Led Supply Chain Makeover That Boosted Speed and Accuracy

Overview

A fast-expanding FMCG company was facing daily slowdowns in its supply chain. Orders were piling up, manual coordination was breaking the flow, and teams were spending more time reacting than planning. They had systems in place, but everything worked in silos such as forecasting, warehousing, routing, procurement and none of them “talked” to each other. 
Even after multiple attempts to streamline processes internally, the delays kept surfacing. Forecast mismatches, routing errors, and last-minute stock shortages were becoming routine, pushing teams into stressful, last-hour fixes.   
The situation soon turned into something bigger. Retailers were getting frustrated, dispatch timelines were slipping, and the business was losing ground to competitors who had a tighter grip on logistics.  

Industry
  • FMCG
Service
  • Agentic AI Automation
1

Full supply chain audit & process mapping

We reviewed scattered operations, identified friction points, and marked areas where delays were frequently repeated. 

2

Intelligent demand forecasting using agentic reasoning

The AI agents tracked seasonality, order behavior and historical patterns to generate more reliable forecasts.

3

Automated replenishment & stock movement triggers

Instead of waiting for manual approvals, agents initiated procurement and inter-warehouse transfers based on real-time stock levels.

4

Smart routing & dispatch planning

Agents analyzed routes, traffic behaviors, historical delays, and delivery priorities to recommend quicker dispatch routes.

The Problem

As order volume grew, the supply chain became slow and unpredictable. Forecasting mismatches, delayed replenishment, and inefficient routing caused missed delivery windows and rising operational costs. Teams had data, but no system that could understand it and take timely actions. 
 

Our Role

  • Forecasting became dynamic instead of static
  • Replenishment ran automatically based on real demand
  • Routing decisions were quicker and more accurate
  • Cross-team communication became smoother

Project Challenges

Frequent stockouts at high-demand locations

Stores faced recurring shortages during peak hours because replenishment was always a step behind demand.

Delayed dispatch planning

Routing decisions depended heavily on manual inputs, causing hold-ups and last-minute changes.

High operational load on teams

Teams were spending long hours coordinating between procurement, warehousing, and logistics.

Zero visibility across the chain

Each department had data, but no unified view of making decisions leading to slow and inconsistent workflow. 

Outcome After Our Implementations

Once the agentic workflows went live, the supply chain began running smoother and with fewer interruptions. Forecasts sharpened, stock movements became timely, and daily operations felt far more manageable for the internal teams. The changes were visible within weeks, not just on dashboards, but in the energy of the people working behind the scenes. 

Supply chain efficiency improved by 47%

Order fulfilment became faster, stockouts reduced, and the overall flow felt more predictable.

Delay-related losses dropped by 23%

With fewer errors in forecasting and dispatch, the business saved a noticeable amount in corrective costs.

8–10 internal hours saved every day

Tasks that once needed long coordination cycles now ran automatically, reducing operational pressure on teams.

How the System Works Today

The system now works with a steady rhythm. Agentic AI keeps track of demand patterns, adjusts forecasts on its own, recommends better dispatch paths, and keeps the inventory moving at the right pace. As a result, the brand runs with far less chaos even as order volumes continue to rise. 

If slow fulfilment cycles, stock mismatches, or routing inefficiencies are holding back your operations, there’s always a smarter way to move forward.