SmartInventoryForecasting

Stock exactly what you need, where you need it. Our AI predicts demand at the SKU-location level, cutting carrying costs by 30% while virtually eliminating stockouts.

Sector

Verified Commerce

Solution

Smart Inventory Forecasting

-85%

Stockouts

-32%

Carrying Cost

-85%

Stockouts

-32%

Carrying Cost

-40%

Waste Reduction

Solution Overview

Capabilities & technology

05 capabilities
01

SKU-level demand forecasting

02

Multi-location inventory rebalancing

03

Seasonal and promotional lift modelling

04

Supplier lead time prediction

05

Automated reorder point optimisation

Technology stack

04 tools
ProphetApache SparkTimescaleDBGrafana
ProphetApache SparkTimescaleDBGrafanaProphetApache SparkTimescaleDBGrafana

Case Study

Reducing Stockouts by 85% for a Supermarket Chain

Executive Summary

A 15-location supermarket chain deployed Smart Inventory Forecasting across all stores. Stockout events dropped by 85%, carrying costs fell by 32%, and weekly waste from overstocking perishables decreased by 40% within six months.

AI layer

Think Multi-Signal Demand Engine

The forecasting model combines point-of-sale data, weather patterns, local events, and promotional calendars using Facebook Prophet enhanced with custom regressors. It generates daily SKU-store forecasts with confidence intervals, automatically adjusting for trends, seasonality, and one-off events.

Blockchain layer

Honesty Auditable Reorder Ledger

Every reorder recommendation, supplier confirmation, and goods receipt is logged to an immutable ledger. Store managers and procurement teams share a transparent view of who ordered what, when, and why resolving disputes and enabling continuous process improvement.

Operational metrics

Metric

Traditional

Hybrid Ecosystem

Stockout Reduction

Baseline

-85%

Carrying Cost Reduction

Baseline

-32%

Perishable Waste

Baseline

-40%

Technical stack

ProphetTime-series demand forecasting
Apache SparkLarge-scale data processing
TimescaleDBTime-series inventory data
GrafanaReal-time monitoring dashboards

2026 Roadmap

Q2 2026: Add automated supplier negotiation recommendations. Q3 2026: Cross-chain inventory visibility for franchise networks. Q4 2026: Drone-based stock auditing integration.

We stopped guessing and started knowing. The forecasting system caught a demand spike from a local event that would have left our shelves empty for three days.
JK

John Kariuki

Supply Chain Manager · FreshMart Kenya

Get Started

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