invent.saleinvent.sale

Less stockouts. Less excess. More money in circulation.

invent.sale shows where you lose sales due to stockouts and where money is frozen in excess inventory.

Money impact per product
Top actions every day
14 days to first results

Sound familiar?

Warehouse overloaded — money frozen

Capital is tied up in excess stock that doesn't sell.

See how we solve this

Empty shelves — lost sales

Customers leave without buying because the product isn't there.

See how we solve this

Orders by gut feeling — stockouts or excess

Without data, every order is a gamble.

See how we solve this

Write-offs growing

Expired and obsolete products eat into your margin.

See how we solve this

Prices and markdowns are late

By the time you discount, the opportunity is already gone.

See how we solve this

What's inside the platform

Idle inventory

Finds excess stock and calculates frozen capital per SKU.

Report: amount, days idle, recommended action
Idle InventoryLive
Frozen$3.2M
SKUDaysAmountAction
A-482194$128KMarkdown
B-310278$86KTransfer
C-7655112$42KRemove
Electronics 45%Apparel 32%Other 23%

Demand forecast

7–30 day plan with range: conservative, baseline, optimistic.

We show accuracy on your data during audit
Demand Forecastv3.2
7d30d
MonTueWedThuFriSatSun
Conservative
420
Baseline
580
Optimistic
740

Price suggestions

Recommends markdowns where they free up cash and recover sales.

Before applying — impact and risk forecast
Price SuggestionSKU
A-4821Premium Headphones X200
Current
$4,990
0 sales/wk
Recommended
$2,990
~8 sales/wk
Expected impact
Margin−8%
Revenue+$68K

Action plan

Every morning — a task list for purchasing, markdowns, and transfers.

Each task — with priority and impact
Action PlanToday: 12 tasks
Order milk 3.2% — 240 units
High+revenue
Transfer 120 units → Store #7
Mediumfrees capital
Markdown 47 idle SKUs
High−write-offs
Stop purchasing 12 SKUs
Mediumfrees cash

One KPI screen

Revenue, margin, turnover, and write-offs — by network and by store.

Updated every 15 minutes
DashboardLive · 15 min
Revenue
$2.8M+12%
Margin
24.5%+1.8%
Turnover
3.2+0.4
Write-offs
180K−22%
Stores
StoreMarginWrite-offs
Central26.1%−18%
North22.8%+5%
Mall West28.4%−31%

Solutions for every role

Buyer

AI generates purchase orders based on forecast, seasonality, and supplier lead times.

up to -60% routine

Ready orders instead of Excel

Commercial Director

All KPIs on one screen — by store, by category, by supplier.

all KPIs on one screen

Network under control

CFO

See frozen capital, turnover, write-off risk — in dollars, not units.

transparency and control

Inventory finances in money

CEO

Chat with AI analyst — ask questions about any store, category, or trend.

AI analyst chat

Control without micromanagement

Results after implementation

Before

10–15 hours per week on manual orders

After

2–3 hours with AI-generated orders

Before

Excess inventory unknown, growing silently

After

Every dead SKU identified with action plan

Before

Write-offs growing, causes unclear

After

Root cause analysis + expiration alerts

Before

Each store orders independently, no coordination

After

Unified AI forecast + automated replenishment rules

From data to actions

1

Connect

15–60 min

1C, MoySklad, Excel, WB, Ozon

2

AI calculates

Automatically

Forecast, dead stock, prices

3

Take action

Every day

Buy, markdown, redistribute

Results in 90 days

Electronics distribution

1 warehouse · 8,000 SKU · 120 clients

The system identified $3.8M frozen in components with expiring lifecycles. AI forecasting adjusted procurement to actual client demand.

Excess inventory
$6.2M$2.4M
Write-offs / mo.
$340K$200K
Stockout rate (key items)
16%8%

−61% excess → $3.8M freed in 90 days

Pharmacy chain

9 pharmacies · 12,000 SKU

59% of inventory turned out to be dead stock. The 4-criteria filter separated truly frozen products from seasonal patterns. Marking down 884 SKUs recovered working capital.

Write-offs / mo.
$60K$36K
Excess inventory
$1.5M$1.1M
Critical stockout rate
12%6%

−40% write-offs, critical stockouts halved

Fashion retail

6 stores · 2 warehouses · 2,000 SKU

Seasonality is the core challenge in fashion: collections go stale in 8–12 weeks. AI seasonality classification identified precise markdown windows for each category.

Frozen capital
$2.1M$0.9M
Inventory turnover
64 days41 days
End-of-season write-offs
22%9%

Turnover 64 → 41 days, write-offs −59%

How much are you losing on inventory right now?

Free audit in 15 minutes. Connect your data in 1 day. No obligations.

See your losses
invent.sale — AI-платформа для управления запасами в ритейле