Results

The numbers tell a story.

Four operations. Different problems. Practical changes.

Sugarwish

Smarter shipping. Better visibility.

Transit 4 → 2.7 days; cost per package ~$9 → ~$7

How it happened

US gifting e-commerce, 500,000 packages a year, 1,000+ SKUs

Problem: High shipping spend, no clear view of where it went
What I did: Shipping spend report; online forecaster showing stock and run-out date per material; analysis for supplier negotiations

Meroda Cosmetics

A different route. A different cost.

Shipping cost per unit $0.29 → $0.03

How it happened

Problem: High freight cost from China
What I did: Moved shipments from air to sea, coordinated suppliers

BRF

Fuller trucks. Lower costs.

Freight costs down 20%

How it happened

Argentina

Problem: High freight costs, trucks leaving underloaded
What I did: Redesigned the logistics network: new routes and better truck fill

P&G

A better provider. A better operation.

Lower logistics cost

How it happened

Chile

Problem: Logistics provider with a high delay rate and recurring service issues
What I did: Changed the provider and renegotiated terms

Worked examples

Illustrative examples with the math shown. Not client results.

Example A — Cash on the shelves (e-commerce)

A Shopify brand with 400 SKUs and $300,000 of inventory at cost. 18% of that stock has more than 180 days of coverage: $54,000 sitting still. Holding inventory typically costs 20–25% of its value per year, so that stock costs $10,800–$13,500 a year just to keep. Clearing half of it frees $27,000 in cash.

Example B — Order entry by hand (distributor)

A distributor gets 60 orders a day by email. Typing each one into the system takes 4 minutes: 4 hours a day, about 1,000 hours a year. At $25 an hour, that's $25,000 a year. A script that reads the email and creates a draft order cuts each one to a 1-minute check: 750 hours and about $18,750 saved per year. Orders that follow a template need no AI. AI only reads the free-text ones.

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