Discovery & Product Workshop
Start wide. Then narrow. We map the use case, the ontology, and the data you actually have, and you leave with a plan to ship.
Start wide. Then narrow. Most projects fail at the scoping stage, not the building stage, because somebody committed to a number before anyone understood the problem.
So we run a short sprint first. We sit with your operators, map the use case, sketch the object model, and go look at the data you actually have rather than the data the architecture diagram claims you have. Those are usually different.
You leave with a real plan: what to build, in what order, what it depends on, and where the risk is. If the honest answer is that this shouldn't be built yet, we'll say that. It's a cheaper conversation now than in month six.
A short sprint to de-risk a complex problem before anyone commits to a build. Every two weeks you get a checkpoint and a decision, so you're never locked in.
Use case mapping
Which decision are we trying to change, who makes it today, and what would have to be true for it to get better. Everything else follows from that.
Ontology sketch
A first pass at the objects, links, and actions. Wrong in places, but concrete enough to argue with, which is the point.
Data reality check
We go into the systems and look. Coverage, quality, refresh rate, and the gaps between what exists and what the plan needs.
Working prototype
Where it helps, something clickable against real data. It settles arguments that a document can't.
Scope and sequence
The thin first slice, then what follows. Ordered so each release stands on its own instead of everything landing at the end.
Risk and dependency register
What could sink this, named early. Access, data gaps, an integration nobody owns, a decision that needs a person who hasn't been in the room.
Narrow first. Checkpoint often. Nothing you can't walk away from.
Week one
Sessions with operators and a look at the real systems. Wide on purpose.
Narrowing
We cut down to the use case that's worth the first build and sketch the model behind it.
Prototype
Something clickable against real data, if that's what it takes to settle the question.
The plan
Scope, sequence, risks, and an honest read on whether to build this now.
What you're handed
A documented use case and the decision it changes
A first-pass object model with objects, links, and actions
A written data assessment with the gaps named
A prototype against real data where it helps settle an argument
A sequenced build plan with risks and dependencies attached
Same discipline, different floor.
- ManufacturingScoping a plant system before anyone commits to replacing what's running.
- HealthcareMapping a finance or supply workflow across facilities that each do it differently.
- GovernmentDe-risking a modernization where the deadline is fixed and the data is a mystery.
- Life SciencesFraming an analytics or trial data problem before the platform decision gets made.
- EnergyTesting whether the sensor and asset data can support the operating picture you want.
Revelation, not reinvention.
We've built this before. These are deployable pieces we bring in on day one instead of billing you to write them again.
Tell us what's breaking. If we're not the right team for it, we'll say so and point you somewhere better.