# What is headless BI? Definition and Examples | Silicon

URL: https://meetsilicon.com/glossary/headless-bi/

> Headless BI is an approach where metric definitions live in a standalone semantic layer that any tool can query, rather than inside one BI tool.

It separates "what does revenue mean?" from "where is revenue displayed?", so dashboards, spreadsheets, AI assistants and applications all share the same definitions.
## Why teams choose it
Companies rarely use one tool for data. Dashboards, spreadsheets, notebooks, customer-facing apps and now AI assistants all ask for the same metrics. Headless BI lets each of them query one set of definitions instead of rebuilding them in every tool.
## The trade-offs
A standalone semantic layer is one more system to run, and each consuming tool needs an integration with it. Some teams find it simpler to use a BI tool whose semantic layer is open, through an API or SQL interface, than to run a separate headless product.
## How Silicon handles it
Silicon's metrics are defined in dbt YAML and served through Silicon's dashboards, Slack and Microsoft Teams, Google Sheets syncs, embedded analytics and the API, so other tools use the same definitions.
FAQ
## Headless BI questions
### What are examples of headless BI tools? +
Cube, the dbt Semantic Layer and AtScale are often described as headless. Several BI tools also expose their semantic layer to other tools.
### Is headless BI the same as a semantic layer? +
Headless BI is an architecture. The semantic layer is the component at its center.
## Related
- Semantic layer ->
- Embedded analytics ->
## Tell us where your data lives today.
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