Semantic Models Overview
Semantic Models transform logical data models (ERDs) into business-ready analytics assets with full execution and publishing capabilities. From business requirements to production-ready DBT pipelines and Snowflake Intelligence integration—all automated.
What Semantic Models Do
From business requirements to queryable AI agent. No manual DBT coding required.
Semantic Models take the ERD from Schema Agents and:
- Capture business requirements through AI-driven interviews
- Generate production-ready artifacts (DBT, lineage, catalog, glossary, metrics)
- Execute DBT pipelines in your data warehouse
- Sync code to Git repositories
- Publish to Snowflake Intelligence or download as packages
The Semantic Models Workflow
Navigate to Semantic Models
From the home page, select the Semantic Models list:
Mission Control
The sidebar tracks progress through the workflow:
UI Tabs
| Tab | Purpose |
|---|---|
| MODEL DETAILS | Basic info, connection selection, context documents |
| BUSINESS REQUIREMENTS | BRD Agent interview and document generation |
| AI MODELING & BUILD | Generated artifacts and DBT execution |
| PUBLISH & REVIEW | Snowflake Intelligence, catalogs, downloads |
Generated Artifacts
From ERD + BRD, ekai generates a complete suite of artifacts:
DBT Project
Complete dbt project with staging, intermediate, and mart models. Ready to run.
Data Lineage
Visual diagram and JSON representation of data flow from source to output.
Data Catalog
Technical and business descriptions for all entities and columns.
Business Glossary
Standardized term definitions linked to data elements.
Metrics & KPIs
Calculated measure definitions with SQL formulas.
Data Validation
dbt tests for schema integrity and business rules.
Publishing Options
| Destination | Status | Description |
|---|---|---|
| Snowflake Intelligence | ✅ Available | Cortex Agents for natural language querying |
| Data Catalogs | On-Demand | OpenMetadata, custom integrations |
| Artifact Download | ✅ Available | Complete package for local use |
Next Steps
- Create Model — Set up a new Semantic Model
- Capture Requirements — BRD Agent interview
- AI Modeling — Generated artifacts
- Execute DBT — Build and run
- Publish — Deploy to Snowflake Intelligence