Decision intelligence

How decisions get made.

We build working models of complex, asset-heavy operations.
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The problem

In these operations, high‑stakes decisions don't get a trial run.

Supply chain network model Manufacturing production line model Mining haulage and shovel operation Warehouse material flow simulation Oil and gas plant, rail, and marine logistics Rail network capacity model Hospital patient flow model Quick service restaurant throughput model

Pick your industry

Capital & capacity

Do we build, buy, or expand, and how much capacity for the years ahead?

Network & footprint

Where should facilities sit, and how should material move between them?

Routing & dispatch

How should trucks, crews, and equipment get assigned as demand shifts day to day?

Throughput & bottlenecks

Where is the real constraint, and what relieves it before we spend on the wrong fix?

Staffing & scheduling

How many people, where, and when, to hit service levels without overspending?

Contingency & risk

What breaks when a site, supplier, or season goes wrong, and what’s the response?

Capital & capacity

Does the network need another distribution center, or better use of the ones we have?

Network & footprint

Where should inventory sit so orders ship on time without stocking it everywhere?

Routing & dispatch

Which lanes and modes should carry which flow when freight rates change?

Throughput & bottlenecks

Which node caps the network, and what happens when we lift it?

Staffing & scheduling

How much labor does each site need to get through peak?

Contingency & risk

What does the network do when a site, supplier, or season goes wrong?

Explore supply chain →

Capital & capacity

Does the next line pay for itself, or does the current one still have room?

Network & footprint

Which plant should build which product, and what does that do to freight?

Routing & dispatch

How should orders be sequenced across cells when the mix changes?

Throughput & bottlenecks

Which operation sets the rate, and what raises it?

Staffing & scheduling

How many operators per shift, with what skills, to keep the schedule?

Contingency & risk

What can we still promise when a supplier or a machine goes down?

Explore manufacturing →

Capital & capacity

Do more trucks add tonnes, or add queue?

Network & footprint

Where should the crusher, stockpile, and load-out sit for the mine plan ahead?

Routing & dispatch

How should the fleet be dispatched as haul distances grow?

Throughput & bottlenecks

Is the constraint the shovel, the haul, the crusher, or the port?

Staffing & scheduling

How many crews and shifts does the ramp-up actually need?

Contingency & risk

What does a weather, rail, or equipment outage cost in shipped tonnes?

Explore mining & energy →

Capital & capacity

Does the automation case hold at the volumes we will actually see?

Network & footprint

How should the building be zoned and slotted for the order profile?

Routing & dispatch

How should picks and replenishment be routed across the floor?

Throughput & bottlenecks

What rate does the building really hold, not the rate on the spec sheet?

Staffing & scheduling

How many pickers, packers, and loaders by hour of the day?

Contingency & risk

What happens to outbound when a sorter or a dock goes down?

Explore warehousing →

Capital & capacity

Does the upgrade add throughput once storage and berth are counted?

Network & footprint

How much storage, and where, between plant, rail, and marine?

Routing & dispatch

How should trains and vessels be scheduled against plant output?

Throughput & bottlenecks

Is the limit the plant, the tankage, the rail cycle, or the berth?

Staffing & scheduling

What crewing does the turnaround plan require to hold the window?

Contingency & risk

What does a rail delay or a weather day cost in deferred volume?

Explore oil & gas →

Capital & capacity

Is new track required, or is there capacity already on the line?

Network & footprint

Where do sidings, yards, and terminals need to sit for the traffic plan?

Routing & dispatch

How should departures, meets, and crews be planned each day?

Throughput & bottlenecks

Which segment or yard sets network fluidity?

Staffing & scheduling

How many crews and where, under hours-of-service rules?

Contingency & risk

What does a blockage or a maintenance window do to the plan?

Explore rail →

Capital & capacity

Do we need more beds, or faster discharge on the units we have?

Network & footprint

Where should services and capacity sit across the campus or region?

Routing & dispatch

How should patients be routed between units to keep flow moving?

Throughput & bottlenecks

Which step creates the wait, and what removes it?

Staffing & scheduling

What staffing mix per shift holds wait times at target?

Contingency & risk

What happens to flow in a surge, an outage, or a season?

Explore healthcare →

Capital & capacity

Does the second drive-thru lane or the new equipment return the capital?

Network & footprint

Where should the next locations sit without cannibalizing the last ones?

Routing & dispatch

How should orders be sequenced between drive-thru, digital, and counter?

Throughput & bottlenecks

Which station sets speed of service at peak?

Staffing & scheduling

How many crew, by daypart and role, to hold service without overspending?

Contingency & risk

What happens on the Friday rush when one station goes down?

Explore quick service restaurants →
Why we exist

Decisions should be made on evidence, not on who's in the room.

So we build decision systems. A model answers the question once. A decision system is that model wired into your data and used by your team, so every high‑stakes call runs through it before it's made.

It connects to the systems you already use.

Your people still make the call. They just make it the same way every time.

How we build it

Simulation
The operation run forward through time, breakdowns and surges included.
Optimization
The best way to deploy capacity, schedules, and routes under real constraints.
AI & machine learning
What's likely to happen next, and what to do about it.
Data science
The drivers and patterns in your data the model should be built around.
Data engineering
Pipelines from your own systems that keep the model current.
Digital twin
The model tied to live data, so every run reflects the operation as it is now.

SimWell Compass

Where your team runs the model. Compass puts it in a browser your planners open the next time the question comes up. Every scenario is versioned and every run is on record, so the next answer takes days, not another project.

Explore Compass →

What our customers are saying

From the people who made the call.

Getting started

How you'd work with us.

  1. Decision Workshop

    Two to three weeks, two days of it on your floor with the people who run it. We map how the work moves end to end, what has to be true at each step, and what it costs when it isn't. You leave with the problems ranked by impact and the first project scoped and priced.

  2. Scoped Project

    A working model of the part of the operation the decision depends on. We run the scenarios and deliver the answer, or your team runs them.

  3. Managed Services

    The model is built and in use. We keep it matched to the operation as it changes, run the scenarios your team brings us, and add the next decision when it's ready.

  4. Licensing & Training

    For teams building the capability themselves. We provide the software, the training, and someone to call when modeling gets hard.

Every decision has a window.

A building with an opening date, a capital request that has to be defended, growth that's already booked.

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