89 days
capital payback: the time it takes money in stock to return as profit
It was 105 days. Capital now turns over 4.1 times a year instead of 3.5.
Case study · Building and launching AI agents for supply chain
AI agents for purchasing: capital pays back 16 days faster, and $100,000 a month no longer sits in the warehouse
We built and launched a team of AI agents for a home goods importer. The main goal: see, forecast and speed up capital payback. The second goal: prevent cash gaps and stockouts. The company sells through its own online store and on more than 10 marketplaces. Every 4 hours, the AI agents check 260+ products and 40+ batches in transit. They show which purchase will return money faster. They work out in advance when to pay and how much. And they warn when it is time to order. A person always makes the decision.
Key figures
$184,000
freed up from inventory in 8 weeks
About $100,000 a month. Profit grew 21% over the same period.
$34
of profit a month from every $100 in stock
It was $29. The same capital earns 18% more.
159
early “time to order” warnings in 12 weeks
Cash gaps and stockouts are visible in advance. At the peak of the season, only 4–5 of 120 fast-moving products were out of stock.
Amounts, sales volumes, products and product names are changed under NDA. Percentages and time in days are real. How we calculated
Summary in 30 seconds
With AI agents, the client’s team
- Sees capital payback for each product and for the whole warehouse: in how many days the money comes back
- Forecasts the payback of each purchase before the money goes to the factory
- Knows 3 months ahead when and how much to pay factories and carriers. A cash gap is visible in advance
- Picks purchases by how fast they return money and fits them into the budget
- Sees stockout risk early and gets a warning weeks before the last day to order
- Orders the batch size the AI agent calculates, not by eye and not by the factory minimum order
- Sees the real profit of each product after delivery and returns
- Asks the AI agent any question in plain words
Main goal
Capital payback: see it, forecast it, speed it up
An importer pays the factory months before the first sale. So the owner has two main questions. In how many days will the invested money come back with profit? And will there be enough money for the next payments? We built the whole project around these two questions.
Capital payback
before105 days
after89 days
This is how many days it takes money in stock to return as profit. Now it is 16 days faster.
Capital turnover per year
before3.5 times
after4.1 times
This is how many times a year money goes around the loop: pay the factory, sell, get the money back.
Monthly profit per $100 in stock
before$29
after$34
The same capital earns 18% more. The company did not add money to the business.
See
The AI capital agent shows how much money sits in each product and in how many days it will come back. Fast money is green, slow money is red. You also see frozen capital separately: products that barely sell.
Forecast
The AI agents calculate the payback of each future batch before you order it. The AI payments agent shows payments 7, 30 and 90 days ahead, and the heaviest day. You see a cash gap weeks ahead, not on the payment day.
Act
You choose the supplier, the delivery method and the batch size by how fast the money comes back. The purchase queue fits the budget. Purchases that return money faster or prevent a stockout go first.
You see a cash gap in advance
The AI payments agent plans the payments for each batch 3 months ahead: payment for goods, balance payments and delivery on arrival. You see the heaviest week today. If money will fall short that week, the team moves purchases in the queue early. Or it agrees on a payment delay with the supplier.
payment for goods payment for delivery
Example with sample data, amounts in thousands of dollars. The “Payment calendar” screen shows the same payments by day.
The challenge
Purchasing from China: every decision costs money 3 months later
This is what a buyer’s week looked like before the AI agents. Laziness was not the problem. A person simply cannot recount 260 products, 40 batches in transit and stock for more than 10 platforms every day.
-
Order
Today’s order decides what you will sell in 3 months. You only see a mistake when the batch arrives or the product runs out.
-
Stockout
A fast-moving product ran out on all platforms at once. Its listings dropped in search. Competitors took the top spots.
-
Payback
The warehouse is full of slow sellers. Money sits in boxes. Nobody knows in how many days it will come back.
-
Cash gap
The factory asks for the balance after production. The carrier waits for payment on arrival. Both need money on the same day. Nobody knows exactly how much the next month will need.
-
Spreadsheets
The purchase plan lives in Excel and in one person’s head. That person goes on vacation, and purchasing stops.
-
Profit
Revenue grows, but free cash does not. Nobody can say which product really makes money after delivery and returns.
With AI agents, the morning looks different. At 08:04 the AI agent has already sent its findings to Telegram.
- Payback calculated
- Payments for 90 days
- Stockout risk found
- Queue fits the budget
People keep the decisions: what to order, from whom and when to pay.
What the AI agents had to do
- See, forecast and speed up capital payback main goal
- Prevent cash gaps: show in advance when and how much to pay main goal
- Warn early about stockouts, given the long delivery times very important
- Decide how much money goes to each purchase and which batches to take
- Plan purchases: what, how much, from whom and when
- Make sure each purchase happens on time
- Track the profit of each product
Stockout risk
A stockout on a marketplace costs more than an empty shelf
The company sells on more than 10 marketplaces and platforms. All channels share one stock. When a product runs out, it disappears from all platforms at once. And marketplaces punish this hard.
- 1
The product runs out
Sales drop to zero on all platforms at once. Shoppers see “out of stock”.
- 2
The listing drops in search
Marketplace algorithms push up products that are in stock and sell steadily. They push listings without stock down.
- 3
Ads stop working
Ad views bring no sales when there is no stock. You have to pause the ads, and the campaign history is lost.
- 4
Competitors take the top
Shoppers switch to similar products. A competitor gets your sales and reviews and moves up.
- 5
Coming back is slow and costly
The new batch arrives, but the listing is now at the bottom. To win back its rank, you need discounts, ads and weeks of time. In season, when competition is tough, this is especially hard.
with AI agents without a warning competitor
An illustration, not client data.
Shoppers do not wait
The classic study by Gruen, Corsten and Bharadwaj (2002) looked at retail stock. On average, about 8% of products were out of stock. Only 15% of shoppers put off the purchase until the product came back. The rest bought from another seller, chose another brand or left without buying.
What the AI agents do against stockouts
- Every 4 hours, compare the date a product runs out with the arrival date of the next batch
- Warn weeks before the last day to order
- Show batches that will not arrive in time, with days out of stock and lost profit
- Track production and delivery delays
- Stop you from ordering too much, so money does not get stuck in stock
In the busiest autumn weeks, 4–5 of 120 fast-moving products were out of stock. That is about 4%.
Why this is hard
Eight rules that must add up to one number
Off-the-shelf forecasting tools assume a simple case: one warehouse, one supplier, delivery in a week. Here everything is different.
10+ platforms
One shared stock for all channels. A stockout hits all platforms at once.
28–113 days
From order to warehouse. Air takes 28 days on average, rail 64, sea 113. Sometimes it takes 8 months.
Minimum order
The factory will not sell less. Often it is more than you need right now.
28 bundles
Each one sells as one product. But in the warehouse it is several different products.
1 product, 3 SKUs
The old and new models sell under different codes. For the forecast, this is one product.
Seasonality
Out of season, a product barely sells. That does not mean it is dead.
2–3 payments
Prepayment on order, balance after production, delivery on arrival. Some payments are partial.
17 warehouses
Own warehouses, marketplace fulfillment and warehouses for defective goods. You cannot sell defective goods.
Each rule is simple on its own. The hard part: they must all add up to one answer. How much to order today, when to pay and what it costs.
Solution
A team of AI agents instead of spreadsheets and manual recounts
An AI agent is a program that collects data on its own, draws conclusions and tells you what to do. We built a team of five AI agents. Each one owns its part of purchasing. They run every 4 hours, never go on vacation and order nothing without your “yes”.
Where the AI agents get data
Accounting system
Orders, stock, unit costs. 2 years of history, about 310,000 orders
Warehouses and platforms
17 warehouses, including marketplace fulfillment. Defective goods count separately
Shipments and payments
Batch statuses, dates, factory invoices, delivery cost for each item
Exchange rates
The National Bank of Ukraine rate updates every hour
Team of AI agents
- data agent
- forecast agent
- purchasing and capital agent
- shipments and payments agent
- AI assistant
What the team gets
Telegram alerts
The AI agent writes on its own: what to order, pay for or pick up
AI agent answers
Any question about the data, in plain words
Findings on screens
Forecast, products, shipments, money, purchase queue, payments
Business owner
Makes the decision. The AI agents never order or pay on their own
Five AI agents and what they do
AI data agent
Every 4 hours, it collects orders, stock in 17 warehouses, batches in transit, payments and exchange rates. It splits bundle sales into the products inside. It merges different SKUs of one product.
AI forecast agent
For each product, it calculates the sales rate, days of stock and the last day to order. It accounts for the season and for rising sales. It is the first to spot a stockout risk.
AI purchasing and capital agent
It calculates capital payback for each product and for the whole warehouse. It sizes the batch with the factory minimum order in mind. It compares suppliers and delivery methods by how fast the money comes back. It fits the purchase queue into the budget.
AI shipments and payments agent
It tracks each batch: production, dispatch, arrival, carrier warehouse. It builds a 90-day payment calendar: prepayment, balance after production, delivery on arrival. It shows the heaviest day, so there is no cash gap.
AI assistant
It answers any question about the data in plain words. It runs “what if” scenarios. It runs on Claude, a language model by Anthropic.
How the AI agents work every day
- STEP 01
Collect data
Every 4 hours, the AI data agent collects orders, stock, batches in transit and payments.
- STEP 02
Look for stockout risk
The AI forecast agent compares two dates: when the product runs out and when a new batch can arrive.
- STEP 03
Size the batch and payback
The AI purchasing agent calculates how much to order and what it costs. It also shows how many days the batch takes to pay back with each supplier.
- STEP 04
Plan payments
The AI payments agent puts prepayments, balance payments and delivery on dates for 90 days. The purchase queue fits the budget, so there is no cash gap.
- STEP 05
Report and answer
The AI agent writes to Telegram, and the AI assistant answers questions. A person makes the decision.
Early warnings
Two dates that decide everything
For each product, the AI forecast agent compares two dates. First, when the product runs out at the current sales rate. Second, when a new batch can arrive if you order today.
Without an AI agent. The order went out when 20 days of stock remained. The batch took 60 days. The product was out of stock for 40 days, listings dropped in search, and shoppers went to competitors.
With an AI agent. The AI agent sent an alert on day 11, when 69 days of stock remained. The batch arrived, and 144 units were still in stock.
stock last day to order: 1,104 pcs
stock last day to order: 1,104 pcs
Last day to order = sales rate × lead time × 1.15. The 15% buffer covers swings in demand and delays on the road. If sales speed up, the AI agent uses the latest 3-week rate. If a product does not sell now because of the season, the AI agent uses the rate for the same period last year.
AI agents warn early, not on the last day
Example: lead time 60 days, sales 20 pcs a day. The last day to order comes when 69 days of stock remain. This is the chain of alerts for one product.
- 34 days before
Forecast screen
“Time to order”
The AI forecast agent adds the product to the plan. You already see how much money to set aside: a batch of about 1,000 pcs, $16,000.
- 6 days before
Telegram
“Reorder soon”
75 days of stock left. The last day to order is close.
- Order day
Telegram and purchase queue
“Order urgently”, if there is still no order
Prepayment to the supplier on its terms, for example 30% on order: $4,800.
- End of production
Telegram and payment calendar
“Pay for production”
Comes 0–3 days before production ends, if the goods are not fully paid. Balance of 70%: $11,200.
- Arrival
Payment calendar
Delivery on arrival: $2,200
The batch arrives while about 9 days of stock are still left. No stockout.
If a batch is late, the AI agent writes “Arrival overdue”. If it will not arrive before the stock runs out, the product moves to the “Won’t arrive in time” group. There you see how many days the product will be out of stock. You also see how much profit the company will lose. This gives you time to bring part of the batch by air, or to raise the price and stretch the stock.
The buyer sets the prepayment percentage from the supplier’s terms. The AI agents use it in the purchase queue: how much we pay now and how much after production.
How payback speeds up
How AI agents speed up capital turnover
A dollar that sits in the warehouse without sales does not work. While a batch is on its way, the money is frozen. AI agents speed up turnover in three ways. They stop you from buying too much. They pick purchases that pay back faster. And they plan payments so there is no cash gap.
The money loop in importing
- Pay the factoryPrepayment on order
- Production1–3 weeks, then the balance
- TransitAir ≈ 4 weeks, sea ≈ 4 months
- Warehouse and salesDelivery is paid on arrival
- Money is backWith profit. Ready to buy again
The faster money goes around the loop, the more times a year it earns profit. AI agents shorten the loop in two ways. They stop you from buying too much. And they show which purchase will return money faster.
Batch payback in simple words
Money in the batch$18,900 Profit per day$172 Days to return110
The AI purchasing agent calculates this number for each product and each supplier. A batch with a 38-day payback returns money almost three times faster than a 110-day batch. So over a year, the same money makes three loops instead of one.
The AI payments agent knows that money goes out in parts: prepayment on order, balance after production, delivery on arrival. So you see how much money you need now. You also see how much you need in one month and in three.
One product, two suppliers
Desk lamp. Sells 15 units a day, 450 in stock.
A · Factory in Ningbo, sea
- Landed price
- $7.30 per unit
- Minimum order
- 1,500 pcs
- Lead time
- 70 days
- Money in the batch
- $10,950
- Profit per day
- $72
Payback 152 days
B · Trading company in Yiwu, air better
- Landed price
- $8.60 per unit
- Minimum order
- 600 pcs
- Lead time
- 30 days
- Money in the batch
- $5,160
- Profit per day
- $52.50
Payback 98 days
Option B costs $1.30 more per unit. But the money comes back 54 days sooner. And $5,790 stays free for another purchase.
We made up the figures in this example. The calculation is real: this is how the AI purchasing agent works it out.
Purchasing budget: what we pay first
There is always less money than you want to spend on stock. You enter the budget. The AI purchasing agent queues purchases by how fast they return money. Urgent items that prevent a stockout stay pinned at the top. The list splits into “pay now” and “waiting”.
Budget
$155,000
$150,770 allocated
- 📌
Wok pan 32 cm payback 110 d $18,900 pay now
waiting - 📌
Lunch box, 3 tiers payback 71 d $12,870 pay now
waiting - 3
Spice organizer payback 38 d $6,000 pay now
waiting - 4
Electric hot plate payback 62 d $16,000 pay now
waiting - 5
Plate set, 18 pieces payback 109 d $23,900 pay now
waiting - 6
Bamboo cutting board payback 118 d $31,900 pay now
waiting - 7
Microwave oven 20 L payback 126 d $41,200 pay now
waiting - 8
Hand blender payback 149 d $49,500 pay now
waiting
Pay now: $150,770. Waiting for the next budget: $49,500.
Telegram
The AI agent writes first when you need to act
Every 4 hours, the AI agents recheck all products and batches. The AI agent sends new findings to Telegram on its own: what to order, what to pay for, what to pick up. You do not need to open the system to see what is urgent.
7 types of AI agent alerts
- Order urgently
- Reorder soon
- Pay for production
- Production overdue
- Batch is 2× the factory minimum
- Arrival overdue
- Pick up from carrier
242alerts in 12 weeks
159said it was time to order
81%closed by the team
AI purchasing agentbot
October 17
🔔 AI purchasing agent: alerts (5)
🔴 Critical (3)
• Order urgently: Wok pan 32 cm
12 days of stock, below lead time (45 d × 1.15). Order now.
• Arrival overdue: Ningbo HW Factory
Planned arrival passed 4 days ago, and the shipment is still not delivered.
• Pick up from carrier: Yiwu KT Trading
5 days at the carrier warehouse. Pick up the goods and close the shipment.
🟡 Warnings (2)
• Reorder soon: Spice organizer
58 days of stock, approaching the reorder point (lead time 50 d).
• Pay for production: Foshan LX Lighting
3 days to production end, only 30% paid. Top up to avoid delaying dispatch.
🔔 AI purchasing agent: alerts (1)
🔴 Critical (1)
• Production overdue: Chaozhou CR Ceramics
Production deadline passed 3 days ago, yet the shipment is still in
“manufacturing”.
AI assistant
Ask the AI agent in plain words
Not everything fits into ready-made reports. You can ask the AI assistant an unusual question. It finds data on products, sales, forecasts and shipments on its own. It answers in seconds. It works in the browser and on the phone.
- Only reads data. It changes nothing, orders nothing and pays nothing
- Runs scenarios: “what if sales grow 30%”
- Marks what is fact and what is your assumption
- Converts amounts to hryvnia at the National Bank of Ukraine rate
- Answers in the interface language: Ukrainian, Russian or English
AI assistantfinds the data itself
Which products are at risk of a stockout, and what will the purchase cost?
2 products are urgent:
1. Wok pan 32 cm. 12 days of stock, lead time 45 days. Batch of 1,400 pcs, $18,900.
2. Lunch box, 3 tiers. 19 days of stock, lead time 50 days. Batch of 1,650 pcs, $12,870.
Total $31,770. Also, a batch of desk lamps is on its way, but it arrives in 27 days. The stock lasts 21 days. The lamp will be out of stock for about 6 days.
What if sales grow 30% in November?
Then the electric hot plate and the spice organizer join the urgent list. Their stock will last 65 and 45 days instead of 85 and 58. Both will fall below the reorder point.
This calculation uses your +30% assumption. It is not a forecast from actual sales.
What is on its way from Ningbo HW Factory now?
2 batches. Rail: 6,100 pcs, planned arrival was October 13, 4 days late. Sea: 10,600 pcs, arriving November 19. On arrival, you need to pay $13,600 for delivery.
AI agent findings on screens
Six screens show everything the AI agents calculate
The AI agents work inside a CRM that we built around the client’s process. The screens show their findings. We replaced the products, suppliers and amounts.
01 Sales forecast
The AI forecast agent sorts products by stockout risk. You see what to order urgently, what won’t arrive in time, what it’s time to order and what is already in transit. Click a tile to keep only that group in the list.
02 Product card
The AI agents’ findings for one product: stock, in transit, days of stock, landed cost, profit for the year and a purchase recommendation. Below are prices from three suppliers with their minimum orders, and the shipment history.
03 Shipments from China
The AI shipments agent tracks each batch: ordered, production, shipped, delivered. Each tile shows how much is paid and how much is still due. Delays show in red.
04 Capital payback
The AI capital agent shows the payback of the whole portfolio and of each batch. You see how much money sits in stock and in how many days it comes back. Fast money is green, slow money is red. A separate tab shows frozen capital.
05 Purchase queue
You enter the budget and the prepayment from the supplier’s terms. The AI purchasing agent puts pinned items first and sorts the rest by how fast they return money. Then it splits the list into “pay now” and “waiting”.
06 Payment calendar
The AI payments agent shows when and how much to pay factories and carriers 7, 30 and 90 days ahead. It also shows the heaviest day. So you see a cash gap in advance. The agent counts real payments, including partial ones.
Results
Capital pays back faster, less money sits in stock, stockouts are under control
We compared 8 weeks from July 27 to September 21: before the season, when demand is flat. Then the company stocked up for the season on purpose. The AI agents helped it do this without slowing down turnover.
| Metric | Before | After | Result |
|---|---|---|---|
| Capital payback | 105 days | 89 days | 16 days faster |
| Capital turnover per year | 3.5 times | 4.1 times | +18% |
| Monthly profit per $100 in stock | $29 | $34 | +18% |
| Money in stock over 8 weeks | $1,817,000 | $1,633,000 | −$184,000 ≈ $100,000 a month |
| Weekly profit, same 8 weeks | $75,100 | $90,500 | +21% |
| Early purchase warnings | over 12 weeks, in Telegram and on the forecast screen | 159 | |
| Fast movers out of stock at peak season | 4–5 of 120 products | ≈ 4% busiest autumn weeks | |
| Profit vs last year, August to October | revenue −8%, orders −21% | +7% | |
| Margin, August to October | 38% | 44% | +6 points |
| Pre-season stock-up, October | $1,633,000 | $2,113,000 | +$480,000 into stock payback did not grow |
Want to see the payback of your own capital? Start with a 60-minute consultation. We will review your purchasing and show what to hand over to AI agents first.
Book a consultationHow we calculated
- Period: daily stock snapshots from July 27 to October 16, 2026. Year-over-year comparison: August 1 to October 16, in 2025 and in 2026.
- Money in stock: stock in warehouses (without defective goods) × landed unit cost.
- Capital payback: money in stock ÷ profit per day. Profit per day: margin per unit × sales rate over the last 2 months. Comparison: July 28 and October 16, 2026.
- Capital turnover per year: 365 ÷ payback. Monthly profit per $100 in stock: 30 ÷ payback × $100.
- Fast-moving product: 10 or more units sold in the last 60 days. Stockout: zero stock in warehouses, without defective goods.
- Warnings: AI agent alerts “Order urgently” and “Reorder soon” from July 23 to October 16, 2026.
- Amounts, sales volumes, products and product names are changed under NDA to protect client data. Percentages and time in days are real.
- Other factors: demand grows in autumn, and prices and the product range changed. The AI agents are not the only reason profit grew. But in this period, the team planned purchases and payments from the AI agents’ findings.
How the project went
From the first data export to AI agents in Telegram: 10 weeks
- WEEKS 1–2
AI data agent
We connected the accounting system. We loaded 2 years of history, about 310,000 orders. We brought the catalog and stock from 17 warehouses together.
- WEEKS 3–4
AI forecast agent
Stock forecast and stockout risk for each product. Shipment tracking with statuses, dates and minimum orders.
- WEEKS 5–6
AI capital agent
Capital payback by product and for the warehouse. Batch sizing. Delivery cost for each item.
- WEEKS 7–10
Alerts and assistant
The AI agent writes to Telegram. The AI assistant answers questions. A purchase queue with a budget. Supply and payment calendars.
- MONTHS 3–5
Fine-tuning
240+ improvements from team feedback. A staff handbook: 46 articles in three languages.
What was hard
The data was wrong on complex products
Bundles, one product under different SKUs, defective goods in separate warehouses. At first, the forecast was wrong on exactly these products. Now the AI data agent splits bundle sales into the products inside. It merges the SKUs of one product and does not count defective goods as stock.
Lead time is not one number
Production plus transit, four types of transport. The AI agent counts lead time from the payment of the first factory invoice, not from the order date. Otherwise the arrival forecast was off by weeks.
Money goes out in parts
Prepayment on order, balance after production, delivery on arrival. Some payments are partial. The AI payments agent counts real payments, not the shipment status.
The team had to trust the AI agents
In the first weeks, the AI agents ran next to the manual plan. We checked the numbers on specific products and removed false alarms. For example, the factory minimum order inflated the recommendations. Now it is only the lower limit.
Seasonality
Out of season, a product barely sells, but it is not dead. For such products, the AI forecast agent uses the rate for the same period last year.
What we need from your team
- Access to the accounting system with orders and stock
- The buyer enters shipments, payments and prepayment terms
- In the first month: regular checks on specific products
Who it fits
Is a team of AI agents right for your business?
It fits if
- You buy abroad, and it takes over 30 days from payment to warehouse
- You sell on several marketplaces, and stockouts hurt your search rank
- You have 100+ products and dozens of suppliers
- Money limits your growth: you cannot buy everything you want, and cash gaps happen
- You want to see in how many days each purchase pays back
- You already keep orders in an accounting system
You don’t need it if
- You have 20–30 products and local suppliers with delivery in a week. A spreadsheet is enough
- You work to order and do not hold stock
FAQ
What owners usually ask
How do AI agents calculate capital payback?
They divide the money in stock by the profit per day. The result is the number of days it takes for the invested money to come back with profit. The AI agents calculate it for each product, for the whole warehouse and for each future batch before you order it.
How do AI agents help avoid cash gaps?
The AI payments agent shows all batch payments 7, 30 and 90 days ahead, and the heaviest day. Prepayment, balance after production and delivery each sit on their own date. The purchase queue fits the budget. So the team does not take on payments it cannot make.
What is a team of AI agents?
It is five programs, each with its own job: data, forecast, purchasing and capital, shipments and payments, answers to questions. Every 4 hours they collect data on their own and draw conclusions. They report them in Telegram and on screens.
How do AI agents help avoid stockouts?
They compare the date a product runs out with the arrival date of the next batch. A product moves to “Time to order” weeks before the last day to order. Then alerts come in Telegram. If a batch is late, the AI agent counts the days out of stock and the lost profit.
How long does implementation take?
The first AI agents went live after 4 weeks. Telegram alerts and the AI assistant came after 10 weeks. After that, we fine-tune the system to your process based on team feedback.
How much of our team’s time will this take?
In the first month, we need access and regular checks with your buyer on specific products. After that, the team enters shipments and payments and makes decisions. Nobody has to calculate in spreadsheets anymore.
What data do we need to start?
Orders and stock from your accounting system. Suppliers, prices, lead times and prepayment terms. If some data is missing, we start with what you have and add the rest as we go.
Will the AI agent order goods or pay an invoice on its own?
No. The AI agents calculate, warn and answer questions. A person places orders and makes payments. The AI assistant only reads data and cannot change it.
What if the forecast is wrong?
The calculation includes a 15% buffer for swings in demand and lead times. The AI agents recalculate everything every 4 hours. If a batch is late or sales speed up, an alert comes to Telegram at the next check.
Can we check the AI agents’ findings?
Yes. The AI agents calculate the numbers with clear rules, so you can check each one by hand. Claude, a language model by Anthropic, understands questions in plain words. If an answer relies on an assumption, the AI assistant says so.
Will AI agents replace the buyer?
No. The buyer stops recounting spreadsheets. Their time goes to talks with factories, quality and new products.
SellerUp · AI automation for e-commerce
A 60-minute consultation on your purchasing
We will find where your money sits, where a stockout is likely and what to hand over to AI agents first. You get a written plan within 48 hours. The price is $249. We credit it towards the next piece of work if it starts within 30 days.
Where to start
A 60-minute consultation: what to hand over to AI agents in your purchasing
A working session on your processes. We look at your purchasing, capital payback, payments and stockout risk. You get a written plan: what to automate first, in what order and what it costs in hours and money.
- 60 minutes, online
- Estimate in hours and money
- Written plan within 48 hours
Consultation · 60 minutes, online
$249 $399
Credited towards the next piece of work if it starts within 30 days
Book a consultation or leave a request belowConsultation request
What eats the most time right now — yours or your team’s?
- Reply within 1 business day
- We send a meeting time and a payment link
- Honest go / no-go answer
- No “boilerplate proposal”