Product overview
From source data to business answers: three layers, one pipeline, with versions and boundaries at every layer.
Three layers
Three layers, one pipeline.
Physical assets, semantic modeling and business consumption. Each layer does its own job, and the boundaries are fixed.
- 01
Physical assets
Sources, workflows, datasets and immutable snapshots. They answer “where did the data come from, and which version?”
- Sources
- Workflows
- Datasets
- Snapshots
- 02
Semantic modeling
Models, dimensions, measures, joins and views. They answer “what does this number mean?”
- Models
- Dimensions
- Measures
- Views
- 03
Business consumption
Perspectives, metrics, reports and APIs. They answer “who looks at what with it?”
- Perspectives
- Metrics
- Dashboards
- APIs
- 01
Consume only through views
Reports, exports, drill-downs, filter suggestions and external systems can query only the members a view exposes.
- 02
The scheduler is the only writer
The API never writes data directly. Anything that needs to write is queued and run by the scheduler.
- 03
Each version has its own life
Data snapshots, model revisions and report versions are different lifecycles, and they never share one “version”.
Good questions
What is Shuzi?
Shuzi connects ingestion, preparation, semantic modeling, analysis and publishing into one pipeline, so teams work from shared metric definitions.
Do I need to know SQL?
Business users can use published reports, the explorer or the AI assistant. Analysts can use SQL during data preparation.
Can the AI see data I'm not allowed to see?
No. The assistant queries as the asker, through the same authorization and row-level permissions.
Can I query from other tools?
Yes. Published models are available through the JSON API, MCP or the PG port. Actual access requires authentication and authorization.
Is the data on this site real?
No. This site uses only local sample data and preset answers. Real data is used after you sign in, under your own permissions.
Take your datafrom tangled to clear.
Try it on sample data first, then bring your own.