Errors surface at the instrument.
A missing resource, unsupported operation or invalid sequence can interrupt a run. You need checks that reflect the behavior your workflow actually depends on.
Verify / Executable digital twins
Check a workflow before the instrument moves.
A workflow can look plausible and still use the wrong resources or operations. We build executable digital twins that model selected instrument capabilities, state and constraints so your team can inspect a proposed plan before approval and dispatch.
verify / Conceptual model
The customer problem
Where the next capability gets blocked.
Hardware access slows development.
Instrument availability limits software iteration. Your team needs repeatable scenarios for interface development, workflow testing and failure handling.
An agent proposes actions you need to inspect.
Before dispatch, you need to understand the planned operations, modeled effects and validation findings, with a clear decision point for the operator.
What we build
A useful scope.
A reviewable result.
Start with the instrument behaviors and failure cases that matter to one workflow. We make the model’s coverage explicit and connect the checks to a useful review experience.
- 01
An executable model of selected behavior
Represent supported commands, resources, state transitions and constraints. Define what the model can check and the physical behavior that remains outside it.
- 02
Workflow dry runs and findings
Evaluate proposed steps against the modeled environment and present useful failures. Support iteration before the team approves the plan.
- 03
Repeatable development scenarios
Provide fixtures for expected operation, unavailable resources and selected errors. Use them to develop the application and integration without requiring hardware for every iteration.
- 04
A controlled route to dispatch
Where included, connect the reviewed workflow to the execution adapter and define handling for changed state, execution errors and uncertain completion.
Relevant engineering
Our demonstration makes planning and modeled validation visible for liquid-handling tasks. It provides a starting point for discussing your instrument and required model coverage.
Before we start
A few practical questions.
Is this a 3D visualization of our instrument?
The core deliverable is an executable behavior and state model. A visualization may help users inspect it, but the value comes from running operations and checking implemented constraints.
What can a twin check?
Depending on the agreed model, checks can cover supported operations, resource availability, state transitions and sequencing constraints. We document the coverage and the assumptions so users understand the meaning of a successful dry run.
Does a successful simulation mean the physical run will succeed?
No. A dry run checks the model and its supplied state. Physical behavior, calibration, consumables and unmodeled conditions require additional checks and evidence for your application.
Can we start without an AI agent?
Yes. An executable twin can support application development, integration tests and operator workflow review independently of AI. An agent can be added when it serves a defined user task.
Your next project
What’s next for your instrument?
Tell us what you want to connect, simplify or automate. Let’s define the first useful step together.