A digital twin that does work, not just demos.
Most digital-twin projects produce a beautiful 3D model that nobody runs operationally. TRACIO designs twins that consume the live event stream you already own, simulate decisions before you make them, and validate process changes against the real plant. Built on the same five-layer architecture as the RTLS programme — they share the event bus, the asset registry, and the semantic model.
Three reasons the model never makes it past the demo.
A twin earns its keep when an operator uses it to decide something. These are the patterns that stop that from happening.
Pretty 3D, no operations
The twin renders gorgeously in the executive briefing room but is never plugged into a live workflow. Nobody on the shop floor opens it. Nobody on the planning team trusts it. It is a visualisation, not a simulation.
Event stream isn’t there yet
The twin needs the live spatial and process event feed that the RTLS, MES, and IIoT programmes were meant to produce. Those event sources are partial, inconsistent, or batch-only. The twin starves.
Twin and reality diverge in 90 days
Layout changes, new equipment, revised SOPs, and vendor swaps drift the physical plant away from the twin. Without a governance model, the twin becomes wrong — quietly, then catastrophically.
Six layers between sensor stream and decision.
We design twins the same way we design RTLS programmes — from the decision back to the data, not the other way round.
The spine the twin runs on
Kafka, Pulsar, or AWS Kinesis — whichever your stack already speaks. The same bus that feeds the RTLS analytics layer feeds the twin. One event model, one source of truth, no parallel pipelines.
What is worth simulating
We start with the decision the twin must support — staffing, layout, throughput, scheduling — and scope the twin around that. Twins that try to model everything end up modelling nothing usefully.
3D model plus meaning
CAD or BIM ingest, asset registry binding, zone semantics, and process metadata. The twin knows what each object is, what state it can be in, and how it interacts with the rest of the workflow.
Discrete-event modelling
AnyLogic, FlexSim, or Siemens Plant Simulation running scenarios against the live state. Test staffing, routing, scheduling, and layout changes before they hit the floor. Output is a decision with a confidence interval.
Twin output, plant outcome
Every simulated decision is logged against the real-world outcome that follows it. The twin’s accuracy is measured continuously, not asserted in a slide deck. Drift triggers alarms, not surprises.
Keeping the twin honest
Change-control workflow that ties physical plant changes to twin updates. Ownership, SLA, and re-validation cadence defined before go-live. Twins age well only when somebody is paid to keep them aligned.
Three ways to bring us in.
Sized to the decision the twin has to support — not to a vendor roadmap.
Twin feasibility · 4 weeks
Decision scoping, event-stream audit, tooling shortlist, and a build-vs-buy recommendation. Output is a signed feasibility pack with a fixed-price build proposal.
Twin design · 8–12 weeks
Full reference architecture, geometry & semantic model, simulation logic, validation harness, and a pilot twin running against the live event bus. Ready to scale or hand to a systems integrator.
Twin build & deploy · 4–6 months
Production twin, integration with planning and ops workflows, operator training, governance model, and 90-day post-deployment validation. Fixed milestones, gated delivery.