Holistics Docs
Holistics is an AI analytics platform built on a uniquely expressive semantic layer.
Most BI tools now ground their AI in a semantic layer. The problem is depth: most semantic layers can only express first-order queries (slice, filter, group), so AI hits a ceiling on real analytical questions like period comparisons, cohort retention, and ratios across grains. It inherits the limits of the layer underneath.
Holistics is built differently:
- A programmable semantic layer. Most BI tools define their semantic layer in YAML configs, which are schemaless, error-prone, and require Jinja workarounds for any reuse. Holistics uses AML, a typed modeling language where models, dimensions, measures, and relationships are first-class language constructs. Modules, extends, partials, conditionals, IDE tooling. A real language built for analytics modeling, not generic key-value configs.
- A composable query language on top. Most semantic layers treat metrics as SQL strings that can't combine or reuse. AQL treats metrics as first-class composable objects, so period comparisons, cohort retention, and ratios across grains stay inside the metric layer instead of leaking into derived tables and spreadsheets.
- Analytics-as-code infrastructure. Most BI tools are UI-first with Git bolted on as an afterthought (if at all). In Holistics, every definition is version-controlled in Git from day one, reviewable through pull requests, and promotable through environments. Code is the source of truth, not a side effect.
This is why trusted AI analytics, governed self-service, and embedded analytics actually work in practice. AI doesn't guess from raw tables; it reasons from the same governed business definitions your team uses. Self-service goes beyond slice-and-dice because cohort retention, period comparisons, and ratios across grains stay inside the governed semantic layer instead of leaking into spreadsheets and one-off SQL.
Where to start
Understand Holistics:
- Why Holistics: what problem we solve and how we solve it differently
- How Holistics works: the architecture and end-to-end workflow
- Key Concepts: terminology and core abstractions
- Product Philosophy: the principles behind our product decisions
Try it hands-on:
- Walkthrough tutorial: build a dataset and dashboard step-by-step
- Sample demo environment: a live, sample workspace you can poke around in
- Playground: write AQL and AML in your browser
If you have a specific evaluation in mind: Holistics AI (AI on the governed semantic layer), Open Semantic Layer (query metrics programmatically), Embedded Analytics (dashboards and AI in your product), or Coming from Looker.
Stay in the loop
- Release notes: what shipped recently
- Roadmap: what's coming next
- Community forum: questions, feature requests, tips and tricks
Older versions of Holistics
This site covers Holistics 4.0. If you're on an earlier version: