Retail & Ecommerce

Demand forecasting, personalization engines, and inventory optimization built on your sales data.

PersonalizationForecastingInventory
The Challenge

Every SKU decision — how much to stock, where, at what price — gets made against a forecast built on last quarter's numbers. By the time a trend shows up in a spreadsheet, the inventory window to act on it has usually already closed.

Our Approach

How We Solve It

Retail margins are won or lost in inventory decisions — what to stock, where, and how much. We build demand forecasting and personalization systems that plug into your existing commerce stack, so pricing, inventory, and marketing decisions are driven by live signal instead of last quarter's spreadsheet.

Capabilities

What We Build

01

Demand Forecasting

SKU-level forecasts across every channel and location, updated continuously.

02

Personalization Engines

Recommendation and merchandising models tuned to your actual catalog.

03

Dynamic Pricing

Markdown and pricing optimization that reacts to real demand signal.

04

Inventory Risk Alerts

Early warning on overstock and stockout exposure before it hits margin.

Delivery Process

How We Deploy It

01

Discover

We study your workflows, data, and systems to find where AI creates real leverage.

02

Design

We architect the models, agents, and integrations around your existing stack.

03

Deploy

The system ships into your environment — on-premises, cloud, or hybrid.

04

Operate

We monitor, retrain, and scale the solution as your business evolves.

Live Example

See It In Action

nezam.ai — retail-ecommerce
>Forecast demand and flag SKUs at risk of overstock or stockout for next month

Here's your Monthly Demand Forecast across 12,600 SKUs:

Forecast Health
93.6%
Forecast Accuracy
214
At-Risk SKUs
$310K
Markdown Exposure
Demand by Category
+18%Apparel
+6%Electronics
-3%Home
+11%Beauty
-9%Grocery
Recommendation: Markdown 40 slow-moving Apparel SKUs before season close — projected to recover $85K in margin.
FAQ

Common Questions

How long does implementation take?

Forecasting and inventory models are typically live within 4-6 weeks once we have access to your sales and inventory data.

Does this work with our commerce platform?

We integrate with your existing commerce, POS, and inventory systems — no migration required.

How do you handle seasonal or promotional spikes?

Models are trained on your historical promotional calendar so seasonal demand is factored in, not treated as noise.

Want this built for your Retail operation?

Tell us about your workflows and we'll scope a tailored AI solution.

Other Industries We Serve