CASE STUDY
LOGISTICS & OPERATIONSAutomating 40% of operational workflows for a regional logistics group
Result
40% of workflows automated
Timeline
14 weeks total (audit + build)
Sector
Logistics & Operations — UAE
The Context
A UAE-based logistics company, 200 employees, growing at 40% year-on-year, had accumulated a significant manual operations burden as it scaled. The company managed regional last-mile delivery, warehousing, and freight coordination for clients across retail, e-commerce, and FMCG sectors.
Leadership had made several attempts to improve operations through software procurement — a new TMS, a customer portal upgrade, and an internal reporting tool. None of the tools had delivered the expected efficiency gains.
The Challenge
Three operations managers were spending more than 60% of their working hours on tasks that required no judgment — data entry, email drafting, status updates, and manual reconciliation. Every new enterprise client added manual volume.
Headcount was growing faster than revenue. The COO knew the business had a structural problem but didn't know which workflows to tackle first or whether AI was the right approach — or just a distraction.
Phase 1: The Audit (6 weeks)
We began with a full AI Automation Audit — mapping every major workflow across the business, from customer onboarding to invoice reconciliation. 23 distinct workflow processes were identified and assessed across 8 business functions.
Each workflow was scored on three dimensions: automation feasibility (technical complexity), business impact (hours saved, error reduction, revenue opportunity), and implementation effort (weeks to build and deploy). The result was a ranked opportunity backlog — 23 processes scored and sorted.
The top 8 opportunities by effort-adjusted impact were selected for the implementation sprint.
Phase 2: The Build (8 weeks)
We deployed AI agents and workflow automation across the top 8 priority areas:
Customer communication AI
LLM-powered classification and response generation for email and WhatsApp — handles status updates, rescheduling requests, and escalation routing
Dispatch notification automation
Automated driver briefings, real-time status notifications to clients, and exception alerts — removing 2+ hours of daily manual comms per dispatcher
Invoice generation pipeline
Automated invoice creation from TMS data, with rule-based exception handling for non-standard client contracts
Account reconciliation
Automated matching of client payments against invoices — flagging discrepancies for human review rather than manual processing of every line
Operations reporting
Automated daily ops summary generation — KPIs, exceptions, and priority actions delivered to management at 7am, every morning
New client onboarding
Structured intake form, automated documentation generation, and system provisioning — cutting 3-day process to under 4 hours
Integration stack: n8n for workflow orchestration, GPT-4o for communication AI, Notion as internal knowledge base for agent context, all integrated with the client's existing TMS and ERP. A 2-week handover and team training phase followed the implementation sprint.
The Outcome
40%
of repetitive ops workflows fully automated
6 FTEs
redeployed to account management and new client onboarding
60% → 15%
reduction in ops manager time spent on manual tasks
14 weeks
from audit kickoff to go-live
"The automation audit changed how we think about our ops team. We stopped adding headcount and started building workflows that run themselves."
— COO, Regional Logistics Group, UAE
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