Industrials & Logistics
Smarter demand. Leaner stock.
Every route optimised.
The Challenge
Industrial businesses lose up to 30% of working capital to static purchase plans that can't respond to real-time demand.
The Solutions
ML-Based Demand Forecasting
From static purchase plans to SKU-level demand forecasts - with automated order recommendations.
Pain Point
Procurement teams rely on static purchase orders, seasonal averages and gut feel - leading to chronic overstock on slow lines and out-of-stocks on high-velocity SKUs.
Our Solution
ML models ingest POS history, promotional calendars, supplier lead times and external signals to generate SKU-level, location-level demand forecasts - driving automated reorder recommendations on a rolling basis.
Impact
ML-Based Order Management
All ordering decisions AI-assisted, Ordering time cut by 60%.
Pain Point
Buyers place orders manually, reconciling supplier catalogues, SLAs and historical purchase data across dozens of SKUs - a process that consumes hours per buyer per week and creates ordering inconsistency.
Our Solution
An AI-assisted ordering platform generates recommended purchase orders based on demand forecasts, current stock positions and supplier constraints - with buyers approving, adjusting or rejecting recommendations with a single click.
Impact
ML-Based Route Optimisation
25% less travel time. More jobs per day. SLA compliance on autopilot.
Pain Point
Field service schedulers assign jobs manually using spreadsheets and local knowledge - leading to inefficient routes, missed SLAs and excess mileage costs across large technician fleets.
Our Solution
ML route optimisation models process job orders, technician locations, traffic patterns, skills matrices and SLA windows simultaneously - generating optimised daily schedules that maximise job completion rates and minimise travel time.
Impact
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