Features

Build, connect and test digital twins

Choose the capability you need, from creating a model to running repeatable tests.

Build twins

Create, review, and reuse digital twin models as practical engineering assets.

Generation

Use your AI agent with SPX MCP to draft reviewable YAML models, run virtual devices and verify their protocol responses.

Models

Keep digital twin definitions structured, readable, reviewable, and version-controlled as normal engineering assets.

Library

Start from reusable device, system, and domain models instead of rebuilding every twin from scratch.

Operate live twin instances and expose the connections your software needs to test.

Runtime

Start, inspect, and control running twin instances with live state, actions, and runtime feedback.

Connections

Expose protocol connections as part of the running twin so software can validate live communication behavior.

Apply scenarios and faults, then inspect the response in live values and logs.

Scenarios

Recreate real-world scenarios, edge cases, timing issues, and failure modes before those problems reach hardware-dependent stages.

Debugging

Inspect live state, protocol behavior, logs, and debugging evidence while twin behavior is running.

Move repeatable validation into Python workflows, Docker, tests, and CI/CD.

Automation

Use Python workflows, repeatable tests, Docker, and CI/CD to turn twin validation into an engineering process.

Looking for embedded testing or virtual commissioning? See how teams use SPX.