CASE STUDY

How AI Agents Are Saving
Amazon Sellers $1,500+/Month —
and Making Supply Planning 20x Faster

March 2026 · 8 min read
The Task: Restock 16 Marketplaces Before Prime Day

Prime Day 2026 is in July. By late March, every purchase order needs to be placed with suppliers so nothing goes out of stock during the biggest sales event of the year.

This seller moves power towers, weight benches, and dip bars across 16 Amazon marketplaces - US, Canada, UK, multiple EU countries, Japan. The job: figure out what's selling where, what's running low, how much to reorder, from which suppliers, how to pack and ship it, and what it's going to cost.

Simple to describe. Brutal to execute. Even harder when the person who does all of this - the supply chain manager based in China - just quit.

Finding a replacement on that timeline wasn't realistic. So the seller tried running the whole thing with an AI agent - a full restock plan for Prime Day - inventory audit, demand forecasts, gap analysis, shipments, financial planning. The kind of work his supply chain manager used to spend a minimum of two weeks on.

Spoiler: the seller built the full restock plan with an AI agent in half a day.

Why This Used to Take Two Weeks

Because you're pulling data from a dozen different sources and none of them talk to each other.

Inventory.

You need to know exactly what's on hand — not just in FBA, but in AWD, at your 3PL, and at your supplier's warehouse in China. For FBA alone, that's a separate inventory report downloaded from Seller Central for every single country. US, Canada, UK, Germany, France, Italy, Spain, Japan — each one a separate download, a separate file. AWD? Separate Excel exports. 3PL warehouses? Often there's no system at all — just receipts, invoices, and your own spreadsheets. You store large batches at a 3PL because it's cheaper than Amazon's warehouses, then drip-feed smaller shipments to FBA as stock runs low. Every move in and out — you're tracking it manually. When you have 16 marketplaces, just collecting this data is days of work.

Shipments in transit.

What's already on the water? What's cleared customs but hasn't been checked in yet? What's sitting in "receiving" at Amazon — which can be 15% of your FBA stock at any given time? You need to account for all of it. Miss a shipment and you'll over-order, tying up cash and racking up storage fees. Forget one and you'll go OOS during Prime Day — the worst possible time.

Sales velocity.

Amazon doesn't give you a velocity report. You take units sold, divide by days, and do it per product, per marketplace. And there are quirks you need to remember for each market. A sale in Italy might ship from a German warehouse — so is that German velocity or Italian? It matters, because your restock math depends on getting this right.

Demand forecast.

You can't just project current velocity forward — Prime Day changes everything. Here's what this seller's forecast looked like:

Per product. Per marketplace. Dozens of calculations, each one requiring historical data you have to dig up manually.

  • Days 1–45(current period): average velocity from Feb–March
  • Days 46–90(pre-Prime season): year-over-year coefficient from the same period last year
  • Days 91–137(Prime Day window): last year's Prime Day multiplier
Gap analysis.

Compare projected demand against available stock — on hand plus in transit plus on order. Identify shortfalls. For each shortfall: how many units to order, from which supplier, how many boxes you need. And the boxes come from a separate supplier — do they even have enough in stock? If not, you need to place a rush order for more boxes before you can even start packing.

Shipment planning.

Calculate CBM and weight per product, figure out what fits in a container and what goes LCL, price out freight, allocate across destinations. And you have to get the consolidation right — customs paperwork costs ~$200 per document whether you're shipping 5 units or 300,000. Send a small batch separately because the timing didn't line up? You just blew up your unit economics. So you need to know exactly when each supplier will have product ready, coordinate pickups, and combine everything into a single customs declaration per destination.

And at every step — double-checking.

In a process this fragmented, mistakes are everywhere. A wrong velocity number cascades through your entire plan. A missed shipment means you're reordering stock that's already on the water. One bad formula in your Excel blows up three tabs downstream.

All of this in spreadsheets. All manual. Minimum 10 working days. And the person doing it? A supply chain manager based in China — someone who can negotiate with local suppliers in their language, get favorable production slots, coordinate consolidation on the ground, AND do all the analytical work in Excel, AND communicate with you in English. That combination of skills doesn't come cheap. $3,000/month minimum.

Half a Day. One AI Agent

The AI agent pulled all the data, ran the full analysis, and delivered a complete supply plan in half a day. This was the first time the seller ran this process with an agent — including trial and error along the way.

Half a Day
instead of 2 weeks
$75K–79K
total COGS planned
137 Days
demand forecast horizon

Here's what came out:

A master Excel workbook with tabs for:

  • Global Summary — every product, every market, current stock vs. projected demand, gaps, order status
  • Detailed inventory breakdown by region: US, CA, UK, EU
  • Box allocation from the packaging supplier (2,000 boxes distributed across products)
  • Combined Shipment Planning — four shipments with CBM, weight, and COGS per product
Device frame AI-generated supply plan: Global Summary across 16 marketplaces
AI-generated supply plan: Global Summary across 16 marketplaces. Click to expand full image

Four ready-to-execute shipments:

US
~61 CBM, 40' HC Container
UK
LCL, consolidated from multiple suppliers
Japan
LCL, consolidated from multiple suppliers
CA
LCL, single supplier
Device frame Combined Shipment Planning — CBM, weight, and COGS per product
Combined Shipment Planning with CBM, weight, and COGS per product. Click to expand full image

Financial plan: Total COGS + shipping in the $75K–79K range. The seller forwarded the numbers to his CFO the same day: "We'll need these amounts by these dates. Start preparing."

137-day demand forecast with year-over-year multipliers across three periods, per product, per marketplace.

Weekly action checklist: What to do today, this week, in April, May, June. Nothing falls through the cracks.

Risk analysis: Box delivery delays, production bottlenecks, slow FBA receiving, weight bench shortages for UK/CA — each with probability rating, impact assessment, and mitigation plan.

The seller spot-checked the key numbers in 5 minutes. Everything matched.

Verifying his supply chain manager's work had never been that fast. It used to mean a few hours of diving into reports and spreadsheets, trying to figure out where each number came from — and often finding errors. With the agent: "Where did you get this number?" — clear explanation of the source and the math. Cross-check it in PROPAMP AI reports. Done.

Accuracy went up too. Hand-built spreadsheets always had gaps — a forgotten lead time, an overlooked capacity limit. The agent caught them all.

Once the seller confirmed the numbers, the agent offered: "I can create the purchase order directly on the platform via MCP." The seller agreed — and the agent built a complete purchase order inside PROPAMP AI: seven products across three suppliers, unit pricing, quantities, four shipment drafts with destination allocation. No manual data entry. No copy-pasting from spreadsheets into forms.

Device frame Purchase order created autonomously by the AI agent in PROPAMP AI
Purchase order created autonomously by the AI agent in PROPAMP AI. Click to expand full image
Device frame Shipment drafts created by the AI agent
Shipment drafts created by the AI agent. Click to expand full image
How It Actually Works

The seller used an AI agent connected to an MCP server from PROPAMP AI. MCP (Model Context Protocol) is what lets the agent plug directly into your Seller Central data, inventory, and sales history — without you manually exporting anything.

Here's what the agent did, step by step:

01
Pulled current inventory

Across all 16 marketplaces — FBA, AWD, 3PL, in-transit shipments. All through the MCP connection.

02
Calculated sales velocity

Per product, per marketplace, using actual sales data from the platform.

03
Built demand forecasts

With three-period YoY multipliers based on prior-year seasonality.

04
Ran gap analysis

Current stock + incoming vs. projected demand. Flagged every shortfall.

05
Planned four shipments

Allocated units, calculated CBM and weight, estimated COGS per shipment.

06
Self-audited

The agent built a dedicated reconciliation tab comparing velocity figures across sources, documenting where each number came from and why.

Device frame AI Agent prompt: project context and supply planning instructions
Part of a prompt the seller created with the AI agent: project context and supply planning instructions. Click to expand the full image

Was it perfect on the first try? No. In the first iteration, the agent used US sales velocity as a baseline for all markets. The seller caught it immediately, told the agent to calculate velocity per marketplace separately, and the fix took 5 minutes.

Another wrinkle: Amazon's own data can be ambiguous — a German warehouse fulfilling an Italian order means the same sale could be attributed to either country. The seller specified the attribution rules once, and the issue was resolved.

The product dimensions and weight data? The seller's first instruction was to pull specs for every SKU through the PROPAMP AI MCP server. Five minutes to verify it was all correct. Done.

The agent also produced a full recommendations document — what to do immediately, what to handle this week, what to schedule for April through June — plus a risk analysis with concrete mitigation steps. The seller reviewed it all. Every recommendation checked out.

Device frame AI-generated action checklist with supply chain risks
AI-generated action checklist with supply chain risks and recommendations. Click to expand full image

Was it perfect on the first try? No. In the first iteration, the agent used US sales velocity as a baseline for all markets. The seller caught it immediately, told the agent to calculate velocity per marketplace separately, and the fix took 5 minutes.

Another wrinkle: Amazon's own data can be ambiguous — a German warehouse fulfilling an Italian order means the same sale could be attributed to either country. The seller specified the attribution rules once, and the issue was resolved.

The product dimensions and weight data? The seller's first instruction was to pull specs for every SKU through the PROPAMP AI MCP server. Five minutes to verify it was all correct. Done.

The agent also produced a full recommendations document — what to do immediately, what to handle this week, what to schedule for April through June — plus a risk analysis with concrete mitigation steps. The seller reviewed it all. Every recommendation checked out.

The Math
Before AI
$1,500/month

SCM Manager salary: $3,000/month

Time for one supply planning cycle: 2+ weeks

Required skills: advanced Excel, supply chain expertise, supplier negotiation, multilingual communication

After AI
$147/month

Claude Code (AI agent by Anthropic): $100/month — an AI agent that runs on your computer, creates and edits files, writes scripts, and connects to external tools through MCP. Think of it as a power user who never sleeps: it can pull data from your email, automate repetitive tasks, build custom reports, and integrate with virtually any system you already use — from Seller Central to messengers to spreadsheets. This seller uses it for supply planning, business automations, and personal tasks. One subscription, unlimited use cases.

PROPAMP AI Pro (MCP server + profit dashboard + inventory tracking): $47/month

Time for one supply planning cycle: half a day

The seller didn't replace the SCM manager with another expensive specialist. He hired a coordinator at $1,500/month — someone who's good at negotiating with suppliers on the ground and organizing shipments, but doesn't need to be an analytics expert. The analytics are now handled by the agent.

Net savings: $1,500/month.

On one operation. The agent is already being applied to other processes.

The hiring pool got massively wider, too. Before, you needed a unicorn: someone fluent in Excel, experienced in supply chain planning, capable of managing supplier relationships, and available at your budget. Now you need a responsible person who can coordinate logistics and communicate well. Lower salary, faster hire, more candidates to choose from.

Tips From a Seller
Who Made the Switch
Treat it like a brilliant new hire on day one.

The agent is incredibly capable, but it doesn't know your specific business rules yet.

Set the ground rules early.

For example: "Calculate velocity per marketplace separately." "Use last year's data for seasonal multipliers." Writing these instructions takes 5 minutes and saves hours.

Don't panic if something's off.

Ask the agent: "How did you calculate this? Walk me through the algorithm." You'll spot the issue in seconds. The fix is another 5 minutes.

You don't need to write perfect prompts.

Just talk to the agent like you'd brief a new team member. It'll help you figure out the details.

Your Move

Supply planning was one operation. The same agent — same subscription, same tool — applies to profit, PPC and returns analysis, out-of-stock prevention, cash flow planning, R&D and product development, and more. Each process you move to an agent is time and money you stop spending manually — and an operation where you're suddenly moving 10–20× faster than competitors who haven't made the switch. That gap compounds.

You don't need to overhaul your business overnight. Start with one task. Run one supply planning cycle with an AI agent. Check the output. Verify the math. Then decide.

The stack that already works:

Claude Code by Anthropic — the AI agent. $100/month, and you'll use it for far more than just supply chain.
PROPAMP AI — the MCP server that connects your agent directly to Seller Central, plus profit dashboards, inventory tracking, payment monitoring, and more. Free 2-week trial.

Your competitors are already cutting costs and moving 20x faster

This isn't theory — you just read the case study.

$150 to test. $1,500/month to gain. That's just from one operation.

How many operations like this are in your business?

2 weeks free
No credit card required
 Included in Pro plan
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