Eliminating 15 Hours of Weekly Dispatch Chaos for a Bathinda Logistics Fleet with Agentic AI
Deploying an agentic AI pipeline to automatically parse WhatsApp freight requests, verify driver schedules, calculate rates, and sync dispatch spreadsheets without manual data entry.
18 Hours
Weekly Hours Saved
< 2 Mins
Quote Turnaround Time
0.0%
Dispatch Error Rate
+24%
Fleet Utilization
Agentic Pipeline
Autonomous Multi-Step Flow
01. Inbound Triage
WhatsApp & Phone Parse
02. Database Match
PostgreSQL Inventory & Calendar
03. Decision Loop
LLM Reasoning & Validation Gate
The Challenge
Dispatch coordinators spent 3 to 4 hours daily copying shipment inquiries from WhatsApp groups into Excel sheets, cross-checking driver availability, and calculating route rates. Typos and delayed responses caused missed loads during busy harvest seasons.
The Solution
We built an agentic multi-step pipeline. When a freight inquiry arrives via WhatsApp Business API, an intake agent extracts route and cargo parameters, a scheduling agent cross-references available fleet GPS locations, and a validation agent drafts an approved rate quotation for team review.
Key Technical Pillars
WhatsApp Business Cloud API integration with webhook event listeners
Structured entity extraction with strict schema validation guardrails
PostgreSQL fleet location and availability state store
Human-in-the-loop approval interface for high-value custom cargo routes
Experience Similar Results
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