> For the complete documentation index, see [llms.txt](https://docs.rootcause.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rootcause.ai/more-details/build-digital-twin.md).

# Digital Twin Build Reference

This section is the detailed reference for building a Digital Twin — the in-depth companion to [Step 5: Build Digital Twin](/user-guide/creating-digital-twin.md). It follows the order you actually work in: choose the data, understand the kind of twin it produces, set the configuration, and tune it for a good fit.

Everything here happens in the twin builder, a four-step wizard (how to build, choose your data, add domain knowledge, review and run). Two paths lead into it for a new twin: **New Digital Twin** on the Digital Twins list, or **Create & build twin** from the Ontology page's recommended datasets. A third, **Modify model** on an existing twin, reopens the same builder seeded with the current configuration and creates a new version when run.

* [Selecting your Data View](/more-details/build-digital-twin/selecting-data-view.md) — the one choice that triggers everything, and what the platform auto-detects when it reads the file.
* [Types of Digital Twins](/more-details/build-digital-twin/twin-types.md) — Static, Temporal, and the two Multi-Environment variants, and how the platform decides which fits your data.
* [Configuration to Build Digital Twin](/more-details/build-digital-twin/build-configuration.md) — every control on the build screen: environments, fields, training options, algorithm versions, and variable roles.
* [Tuning for Fit](/more-details/build-digital-twin/tuning-for-fit.md) — the change-config, retrain, read-fit loop, and the levers that move the result most.

Once a twin is built, see [Configuration for Existing Twin](/more-details/digital-twin/configuration.md) and the other Digital Twin pages for working with it.