AI-Driven Inventory and Pricing
Forecasting and pricing support that works off your sales history: when to reorder and how much, which lines are turning into dead stock, and where a price change is worth considering, always with a person approving the call.
Fixed-calendar stock and price reviews miss the moment
Reviewing reorder points once a quarter and prices twice a year means stockouts on the lines that took off and cash tied up in the ones that did not, plus prices that lag demand and cost. The data to do better is already in your order history and product records. The job is to turn it into specific, timely suggestions, and to keep a person in the loop so the store does not make strange automated decisions on its own.
What we build
- Demand forecasts per SKU that account for trend and seasonality
- Reorder-point and reorder-quantity suggestions tied to supplier lead times
- Slow-mover and dead-stock flags with markdown suggestions to clear them
- Price recommendations with margin, elasticity signals, and competitor context where a feed exists
- An approval queue so every stock or price change is reviewed before it goes live
- Alerts for the cases that need attention now, not a report nobody opens
How the build runs
- 1
Assess the data
3–5 daysWe review order history, current stock records, supplier lead times, and cost data for completeness.
- 2
Build the forecasts
1–2 weeksPer-SKU demand models are fitted and back-tested against your own history before anyone relies on them.
- 3
Add pricing context
3–5 daysMargin rules, elasticity signals, and any competitor feed are combined into price suggestions with reasoning.
- 4
Put a human in the loop
2–3 daysSuggestions land in an approval queue with the why attached, and your team accepts, edits, or rejects each one.
- 5
Monitor and adjust
OngoingForecast accuracy is tracked over time and the models are adjusted as patterns shift.
How we deliver
- 1
Discovery & Scoping
1-3 daysWe start by understanding the actual problem and your existing systems, not just the brief.
- 2
Architecture & Plan
2-4 daysWe map the technical approach and integration points before any code gets written.
- 3
Build
1-8 weeks, scoped to your projectAI-augmented development that moves fast without skipping review.
- 4
Test & Launch
2-3 daysReal testing against real scenarios before it touches a live user.
- 5
Tune & Support
OngoingWe monitor and refine in the weeks after launch. This isn't a handoff and disappear.
What you get out of it
- Fewer stockouts on fast movers and less cash stuck in slow ones
- Reorder decisions backed by a forecast instead of a gut call
- Price changes considered when demand or cost moves, not on a fixed date
- A clear audit trail of what changed, when, and why
Questions we get about this
No. By default the system only suggests, with the reasoning shown. A person approves, edits, or rejects each change. Full automation within tight limits is possible later if you want it, but it is not the starting point.
More in AI-Powered E-Commerce
Ready to scope ai-driven inventory and pricing?
Send us the details of your setup: the tools, the volume, the workflow. We'll come back with an honest assessment and a fixed quote.