Feature

Code-Defined Twin Models

Represent twin behavior in structured definitions that can be reviewed, versioned, generated, and extended over time.

Product capability

Code-Defined Twin Models keep digital twin behavior in structured definitions that engineers can review, version, and extend. This makes models part of the engineering workflow rather than a separate specialist artifact.

Common use cases

Review twin behavior in code review.
Version model changes with the rest of the project.
Use structured definitions as inputs for AI-assisted generation.

Related protocol examples

Related quickstarts

Related features

AI-Assisted Twin Generation

Generate digital twins from documentation, specifications, and engineering requirements with structured, reviewable outputs.

Model Library

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

Automation, Python & CI

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

Related protocols

MQTT Simulator

Simulate MQTT device behavior with realistic topic updates, retained messages, reconnect flows, and automation interactions.

Modbus TCP Simulator

Emulate Modbus TCP behavior with realistic registers, timing, scaling, reads, writes, and fault conditions.

Related guides

Modbus TCP Simulator in 5 Minutes

Launch a Modbus TCP simulator in SPX, inspect live register behavior, and validate client interactions without hardware.

Developer resources

Model Language

The YAML modeling language used to define attributes, actions, communication, scenarios, and hooks.

Model Catalog

Cataloged SPX models across building, industrial, energy, lab, and environment domains.

SPX Examples on GitHub

Runnable examples, tests, profiles, and implementation patterns for SPX SDK and server workflows.