Retail Inventory Intelligence

AI for shelves, DCs, and e‑commerce. Forecast. Allocate. Optimize.

Unify POS, e‑commerce, and supply signals to cut stockouts, markdown waste, and carrying cost—with store‑level forecasts, smart replenishment, and omnichannel allocation your planners can trust.

From signal to shelf — one intelligent loop.

OMNI_SUPPLY_CORE_V2
Demand forecast accuracy96.8%
Stockout risk reduced−41%
2.1M SKUs Replen in sync

Dummy control tower — styled like a live ops console.

Why this matters

Margin leaks from the wrong inventory in the wrong place. Our retail AI stack helps you:

Right stock, right store

Granular forecasts by SKU, location, and channel—not one-size spreadsheets.

Fewer stockouts

Earlier signals on velocity shifts, promos, and seasonality.

Less waste & markdown

Align buys and transfers before inventory ages out.

Faster planners

Recommendations and guardrails your team can approve in minutes.

Platform depth

Solving the Retail Inventory Puzzle

Stores and DCs drown in spreadsheets while customers walk out empty-handed. Lakshya’s retail AI targets the operational breaks that erode margin—signal, forecast, and execution in one loop.

Overstock & markdown spiral

Problem: Buys and transfers lag reality; slow movers tie up capital.

Solution: Probabilistic demand + clearance scenarios before you commit inventory.

Stockouts & lost sales

Problem: Store and channel allocations miss local demand curves.

Solution: Omnichannel allocation with replenishment cadence tuned per node.

Siloed demand signals

Problem: E‑commerce, stores, and wholesale teams optimize in isolation.

Solution: Unified feature store and planners’ cockpit for one version of demand.

View Medical AI

Omnichannel Demand Hub

Live performance — illustrative dashboard

Forecast accuracy (WAPE) 96.8%
Inventory turns uplift +22%
2.1M SKUs optimized
1,850+ Stores & nodes

Intelligent retail supply engine

Built for omnichannel operators. Our platform combines forecasting, optimization, and execution workflows to:

  • Ingest POS, web, marketplace, and shipment signals in near real time
  • Generate hierarchical forecasts down to store–SKU–week
  • Recommend orders, transfers, and allocations with guardrails
  • Surface exceptions, lost sales, and inventory health in one console

Key features

From demand sensing to store replenishment—designed for retail operators, not slide decks.

Demand sensing

Detect shifts from promos, weather, events, and competitive moves earlier.

Assortment & allocation

Right depth per door, channel, and region—balanced to service targets.

Markdown & lifecycle

Stage pricing moves before inventory becomes distressed.

Replenishment automation

DC-to-store flows with lead-time aware targets and minimum presentation rules.

Executive & store dashboards

Health of inventory, service level, and waste in views each role actually uses.

Who it’s for

Teams that live or die on in-stock and inventory productivity.

Big-box & specialty retail

Grocery & convenience

Apparel & seasonal brands

DTC & hybrid operators

Stores + e‑commerce + wholesale

Outcomes operators measure

28% Avg. revenue uplift scenarios
94% Target in-stock service band
35% Waste & spoilage reduction
Faster replenishment cycles

How it works

A straight-line path from messy signals to confident execution.

1

Connect POS, OMS, WMS, and partner feeds

2

Harmonize & enrich demand features

3

Generate forecasts & scenarios

4

Optimize orders, transfers, allocations

5

Measure, learn, and tighten every week

Why Lakshya Technologies

Enterprise-grade AI delivery—not a one-off model in a notebook.

  • Deep experience across retail, healthcare, and finance data platforms
  • MLOps, monitoring, and governance baked into rollout
  • Cloud-native, API-friendly integration with your ERP & planning tools
  • Dedicated solution teams for tuning and change management

“Inventory intelligence your stores can feel on the shelf.”

Ready to modernize retail supply decisions?

See the dummy dashboards come to life with your data in a guided pilot.