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CASE STUDY

LOGISTICS & OPERATIONS

Automating 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

Find the workflows your operations team shouldn't be doing manually.

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