
Demand forecasting and route optimisation, built on your live operational data — each one sharper because the other exists.

A regional FMCG distributor serving 2,000+ retail customers across Southeast Asia came to us with two questions that run the whole business: how much will each customer buy, and how do we serve every one of them, profitably, every day.
Neither is a reporting question. They are operational decisions — made by hand, slowly, at a scale people can't sustain.

Demand was sharply concentrated and history lengths varied enormously. One global model would have been wrong for almost everyone.
Steady buyers, lumpy buyers, sparse accounts, churned accounts, and dormant edge cases each have fundamentally different statistical signatures. A single model averages them all — and is wrong for almost everyone.
Every method choice is decided by back-testing on held-out history, not assumption. The model that wins on your own data is the model that runs.
The vans ran roughly half-full on cargo — but close to 90% full on driver time. The binding limit was never truck space. It was hours in the day.
The lever that swings fleet size, coverage and revenue-at-risk is not how much you can load — it's how many minutes each store visit takes. That single diagnosis reframed every decision.

The demand forecast tells the route planner how much to carry and where it's going — routes built on demand you can trust.
The route plan tells the forecast what's actually deliverable — a forecast grounded in delivery reality.
Run apart, each is useful. Run together, each makes the other more accurate. The compounding effect is the product.

PDPA-aligned and governed. The forecasting and routing engine runs on infrastructure KMS manages — scheduled, monitored, and accountable to the work it's built for.
Multi-agent AI turns these engines into daily workflows your field team can actually execute — not a dashboard to interpret.
Your existing analytics — Qlik, Power BI, your ERP — stay exactly where they are. We connect directly. No Excel uploads, no migration project.
Customer-level demand forecast horizon, re-running on schedule.
Individual customer-level forecasts, not aggregated averages.
KMS keeps the engine running, governed and accountable.
A six-month, customer-level forecast and a constraint-aware delivery plan, re-running on a schedule and writing results back into the field team's systems. Built on real operational data, deployed and governed by KMS.

We'll tell you upfront rather than sell you a system that can't earn its keep.
Confirm real constraints with your operations team. Identify the one number the fleet answer pivots on: true service time per stop.
Build and back-test models on your own held-out history. Every champion beats the naive baselines before deployment.
Go live with humans in the loop. Planners can override any customer, any month — and the override survives every re-run.
Hand the field team a plan they can execute. Results written back into their systems automatically.
KMS keeps the engine running, re-running on schedule and accountable to the work it's built for — indefinitely.
Scope and connect → model and validate on your own held-out history → deploy with humans in the loop → hand the field team a plan they can execute. Then KMS keeps the engine running, re-running on schedule and accountable to the work it's built for.
Book a scoping call. We confirm the real constraints with your operations team — including the one number the whole fleet answer pivots on: true service time per stop. You get a written proposal within 48 hours. Then we engage.
No. Qlik, Power BI and your ERP stay where they are; we connect directly. No migration, no rip-and-replace.
On Azure in Singapore, hosted and managed by KMS, PDPA-aligned and governed.
Model choice is decided by back-testing on your own history — every champion beats the naive baselines before it runs in production.
Forecast to zero, flagged for review, never silently deleted. Your planners see them clearly.
Yes. Any customer, any month — and the override survives every re-run. The system works with your team, not around them.
We confirm scope on the call and give a written proposal within 48 hours. Timeline depends on data readiness confirmed at scoping.
Start with one number: the true average service time per stop. We don't guess it. We confirm it, and the model gives a precise answer either way.
Built on your real operational data, back-tested against your own history.
Live in the field, writing results back into the systems your team already uses.
KMS manages and governs the engine — re-running on schedule, indefinitely.
End-to-end AI solutions built on your operational data.
Rapid proof-of-value pilots scoped and delivered in weeks.
Hands-on sessions to align your team on AI opportunity and approach.
Connected analytics that stay where they are — enhanced, not replaced.
Demand forecasting and route optimisation for distribution businesses.
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Singapore-based. Deployed across Southeast Asia.
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AI Demand & Route Solution for Distribution