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AI Demand & Route Solution for Distribution
Two engines. One distribution business.
Demand forecasting and route optimisation, built on your live operational data — each one sharper because the other exists.
A dashboard tells you what happened. It can't decide what to do next.
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.
We don't run one model. We route every customer to the method proven best for its own pattern.
Demand was sharply concentrated and history lengths varied enormously. One global model would have been wrong for almost everyone.
Why segmentation matters
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.
How the champion is chosen
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 fleet was time-constrained, not volume-constrained.
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 reframe that changes everything
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.
Two engines that feed each other.
Demand → Route
The demand forecast tells the route planner how much to carry and where it's going — routes built on demand you can trust.
Route → Demand
The route plan tells the forecast what's actually deliverable — a forecast grounded in delivery reality.
Run Together
Run apart, each is useful. Run together, each makes the other more accurate. The compounding effect is the product.
Engineered, hosted, and accountable.
KMS-hosted on Azure Singapore
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.
Allmates AI Coworker Layer
Multi-agent AI turns these engines into daily workflows your field team can actually execute — not a dashboard to interpret.
No rip-and-replace
Your existing analytics — Qlik, Power BI, your ERP — stay exactly where they are. We connect directly. No Excel uploads, no migration project.
Live, across Southeast Asia.
6mo
Forward Forecast
Customer-level demand forecast horizon, re-running on schedule.
2000+
Retail Customers
Individual customer-level forecasts, not aggregated averages.
24/7
Managed Operations
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.
Built for distribution. Honest about where it fits.
A good fit
  • A sizeable retail customer base
  • A delivery or van-sales fleet
  • Two-plus years of order history
  • Existing analytics you don't want to replace
Not yet a fit
  • A handful of customers
  • No fleet to plan
  • No order history to learn from
We'll tell you upfront rather than sell you a system that can't earn its keep.
1
Phase 1: Scope & Connect
Confirm real constraints with your operations team. Identify the one number the fleet answer pivots on: true service time per stop.
2
Phase 2: Model & Validate
Build and back-test models on your own held-out history. Every champion beats the naive baselines before deployment.
3
Phase 3: Deploy
Go live with humans in the loop. Planners can override any customer, any month — and the override survives every re-run.
4
Phase 4: Field Execution
Hand the field team a plan they can execute. Results written back into their systems automatically.
5
Managed Operations
KMS keeps the engine running, re-running on schedule and accountable to the work it's built for — indefinitely.
Four phases, then managed operations.
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.
A simple way in.
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.
Questions we're usually asked.
Do you replace our existing analytics?
No. Qlik, Power BI and your ERP stay where they are; we connect directly. No migration, no rip-and-replace.
Where does our data live?
On Azure in Singapore, hosted and managed by KMS, PDPA-aligned and governed.
How accurate is the forecast?
Model choice is decided by back-testing on your own history — every champion beats the naive baselines before it runs in production.
What about customers who've stopped buying?
Forecast to zero, flagged for review, never silently deleted. Your planners see them clearly.
Can our planners override it?
Yes. Any customer, any month — and the override survives every re-run. The system works with your team, not around them.
How long until it's live?
We confirm scope on the call and give a written proposal within 48 hours. Timeline depends on data readiness confirmed at scoping.
Not pilots that stall. Systems — engineered, deployed, accountable.
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.
Engineered
Built on your real operational data, back-tested against your own history.
Deployed
Live in the field, writing results back into the systems your team already uses.
Accountable
KMS manages and governs the engine — re-running on schedule, indefinitely.
KMS — Unlocking the Power of AI for Analytics and Automation
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Rapid proof-of-value pilots scoped and delivered in weeks.
Workshop
Hands-on sessions to align your team on AI opportunity and approach.
Analytics
Connected analytics that stay where they are — enhanced, not replaced.
AI Demand & Route Solution
Demand forecasting and route optimisation for distribution businesses.
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KMS
Knowledge Management Solutions
Singapore-based. Deployed across Southeast Asia.
Master Reseller for Allmates.ai across Southeast Asia.
Unlocking the Power of AI for Analytics and Automation.
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AI Demand & Route Solution for Distribution
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