Semantic Layer Engineering Consulting
We build and certify the semantic layer that defines your metrics once so every tool and AI agent computes them the same way. Warehouse-native and governed.
What this service covers
- semantic layer engineering
- semantic layer consulting
- metrics layer
- headless BI
- dbt semantic layer
- certified metrics
- business logic for AI
- metric definition layer
Frequently asked questions
What is a semantic layer?
A semantic layer is where business metrics are defined once and served to every downstream tool. Instead of each dashboard or AI agent re-deriving revenue or churn, they all read the same certified definition, so the numbers agree and AI can be trusted to reason on them.
Why does AI need a semantic layer?
An LLM pointed at raw tables guesses at what your business terms mean, which is how you get confident wrong answers. A semantic layer gives the model the certified definition of churn, active patient, or ARR, so it reasons on your logic instead of inventing its own.
Do we need to replace our BI tool or warehouse?
No. The semantic layer sits on top of the warehouse you already run and under the BI tools you already use. We build it in dbt, the warehouse, or your tool's modeling layer, whichever fits your stack.
How is this different from a data dictionary?
A data dictionary is a document nobody enforces. A semantic layer is executable: the definition lives in code, every tool reads from it, and a change runs through tests and an approval before it reaches a report.
How long does it take?
We certify the 15 to 40 metrics that drive decisions first, which is usually an 8 to 12 week engagement. Less critical metrics follow once the foundation and the governance model are in place.
Who owns the layer after the engagement?
You do. Every metric gets a named internal owner, and we run an enablement transfer so your team can extend and change the layer without us.
Request the 30-day Analytics Truth Audit to scope this engagement for your environment.