Case Study · Supply Chain
Eight hours a week.
Down to fifteen minutes.
A large North American pallet provider hired us to show what pragmatic AI looks like on existing Microsoft infrastructure — no big platform swap, no unnecessary spend. The first proof of concept ran in three weeks.
The Situation
Real AI value on the tools they already owned.
This client is one of the largest pallet providers in North America — operations spanning the US, Mexico, and Canada, serving some of the biggest names in CPG and retail. They had an active Microsoft investment and a leadership team that believed AI could move the business forward. What they didn't want: a bloated transformation program, a new vendor stack, or AI initiatives that generated slide decks instead of outcomes.
They hired CommonLogic with a clear mandate: start small, find individual wins through focused helper agents, and demonstrate how AI can scale cross-functionally — without unnecessary investment or complexity.
The engagement was also designed to produce something transferable: guidance their own team could act on independently, governance and licensing clarity, and reusable patterns for future initiatives.
AI enterprise value guidance
Concrete direction on where AI creates measurable impact across their teams — not a generic framework, mapped to their actual processes.
Licensing, cost & governance clarity
What will Azure AI consumption actually cost? How should AI usage be governed across the org? These questions answered before going live, not after.
Transferable how-to documentation
Everything needed for their team to run and extend the solutions independently — architecture docs, prompt patterns, runbooks.
Cross-pollination with their team
Work done alongside internal staff, not handed over cold. The goal: build internal AI competency, not dependency on an external firm.
Our Approach
How we ran the engagement.
We followed our POINT delivery methodology — five steps from problem definition to measured expansion. Think pilot, not platform.
Prioritize the Problem
Scoped the target to a single, high-frequency pain: routine client communications were consuming eight hours of a skilled employee's week. We aligned with the CIO and VP of Operations on the KPI that would move — not eliminating headcount, but reclaiming time for higher-value work.
Outline the Win
Built a one-page value case for the ELT. Quantified the efficiency gain, mapped it to the Microsoft tools already licensed, and got executive sign-off before any development started. The POC criteria were defined in advance: three weeks to a working agent, measurable hours saved.
Implement Rapidly
Deployed an assistant-style AI agent to automate routine client communication tasks — status updates, standard inquiries, scheduled follow-ups. Built on their existing Microsoft infrastructure. Nothing net-new to procure or govern. Three weeks from kick-off to production.
Normalize the New Workflow
Trained the team on human-in-the-loop review — the agent drafts, a team member approves before anything goes out. Embedded the workflow into existing daily routines. Usage became habitual within two weeks of go-live.
Track and Expand
Measured: eight hours per week reduced to fifteen minutes. ROI demonstrated. The CIO used those numbers to unlock the next phase. Scope expanded to cross-functional workflows across operations, logistics coordination, and supplier communication. Engagement is ongoing.
Learn more about the POINT framework → How We Deliver
The First Win
Three weeks.
One agent. Measured.
The first POC targeted a single, well-defined pain point: routine client communications were eating eight hours of a skilled employee's week — status updates, standard inquiries, scheduled follow-ups. Manual, repetitive, and exactly the right fit for an AI agent.
We built an assistant-style AI agent on their existing Microsoft stack. The agent drafts outbound client communications; a team member reviews and approves before anything is sent. Nothing automated beyond the human's view — true human-in-the-loop.
Delivered in three weeks. Running in production on day twenty-one.
Before
per week on routine client communications — manual, undifferentiated work
After · Week 3
per week — review and approve drafts, then move on to higher-value work
Outcomes
The POC worked.
So we kept going.
The CIO and VP of Operations used the POC results to green-light the next phase. A successful proof of concept with real numbers behind it is the fastest path to expanded scope — and that's exactly what happened.
POC delivered in 3 weeks
From kick-off to production in 21 days. Defined scope, defined timeline, no surprises.
Measurable efficiency gain documented
8 hours per week → 15 minutes. Numbers the ELT could act on — not projections, actual results.
Engagement scope expanded
Initial win unlocked cross-functional scope: operations, logistics coordination, supplier communications — all on the roadmap.
Client engagement is ongoing
CommonLogic is still embedded with this client — building on the foundation and systematically extending AI adoption across the business.
ELT sponsorship: CIO + VP Operations
C-suite and operational leadership aligned. Not a one-off IT experiment — AI adoption owned at the business level.
Want results like this
for your team?
We'll help you find the highest-value AI opportunity in your business, build a proof of concept in weeks, and measure the outcome before you commit to anything larger.
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