.view.yml and
.topic.yml schemas into dialect-specific SQL — resolving joins from entity
definitions and protecting against fan-out — so a measure means the same thing
everywhere and no query is hand-written or hallucinated. It’s built to be
embedded, scripted, or called by agents.
Everything the World Model does — the
semantic model, the
metric tree, the entity graph — is
compiled by Airlayer.
What it does
- Deterministic SQL. Given the same request, Airlayer always emits the same SQL — there’s no LLM in the compilation path, so results are reproducible.
- Automatic joins. Entity declarations tell Airlayer how views relate, so it builds the join path for you and guards against fan-out double-counting.
- Dialect-aware. The same definitions compile to BigQuery, Snowflake, Postgres, DuckDB, and more.
- Embeddable. Airlayer runs in-process as a library or CLI, so agents and apps can compile and run semantic queries without a separate service.
airlayer on GitHub
In-process semantic engine that compiles YAML schemas into dialect-specific
SQL. Open source.
Next steps
The semantic model
Define the views Airlayer compiles
The World Model
What Airlayer’s output powers