This page covers Data Validation concepts, core objects, setup flow, and project-level entry points. It does not cover dashboard widget validation paths; for widget-based validation, see Validation Widgets in Dashboards (draft).Documentation Index
Fetch the complete documentation index at: https://docs.speckle.systems/llms.txt
Use this file to discover all available pages before exploring further.
Why teams adopt it
Use it when validation rules must stay stable across iterations or across people—for repeatable QA, shared predicates and thresholds, and pass-rate comparison as versions ship.Core objects
Validation checks execute saved rules against tracked models when you run manually or when auto-run triggers on new versions. Standards store project-scoped rule templates that you reuse when creating checks. A result captures one completed run with scores, per-rule statuses, counts, and failing element links. History orders past results for a check so you can compare trends across versions.Quickstart
The end-to-end flow is the single setup path from authoring to result review.End-to-end flow
You need at least one published model version in the project.Save
Check: name, optional description, scoped models, manual or auto-run on new
versions. Standard: stored for spawning checks later.
Track results
Open the check result page; expand rules and models to see filter-step counts when
debugging failures.
After the first pass
For authoring details and run analysis, see Checks, Standards, and Viewing Results.Navigate from project sidebar
In the project sidebar:- Data Validation
- Run check — draft / preview without persisting yet
- Checks — saved checks (rename only in v0; see Checks page)
- Project standards — create / import standards
Progressive implementation sequence
Explore — run preview on real revisions first so scope errors show before saving (Run a first check). Persist — save against tracked models so reruns stay comparable over time (Operate checks over time, Practical review flow). Scale — reuse one standard across checks so shared logic stays aligned (Standards to checks flow).Start here
Run and manage checks
Rules, preview, thresholds, saves, tracked models.
Create project standards
Templates and interoperability imports inside a project.
Interpret results
Latest versus history, statuses, drills.
Using dashboard widgets instead?
Dashboard widget validation is documented in Validation Widgets in
Dashboards (draft).
Plan availability
Caps differ mainly on whether checks persist and whether multiple models attach per check.What Model Validation (beta) features do I get on each plan?
What Model Validation (beta) features do I get on each plan?
Explore (Free): in-session authoring and preview only; no saved checks or preserved
history.Team (Business): saved checks and trends for one tracked model per check.Enterprise: multi-model checks and project standards on the same authoring
stack.
FAQ
Should I start with a check or a standard?
Should I start with a check or a standard?
Start with a check when you are validating one concrete requirement against
active models. Start with a standard when you want reusable rules that multiple
checks can inherit.
Do checks run automatically?
Do checks run automatically?
Checks can run in manual mode or auto-run on new model versions, depending on check
trigger settings.
Where do I inspect detailed outcomes?
Where do I inspect detailed outcomes?
Open the check detail page to inspect latest and historical rule outcomes. See
Viewing Results.
Can I still use dashboard widgets for validation?
Can I still use dashboard widgets for validation?
Yes. Widget-first validation is documented in Validation Widgets in
Dashboards.