Semantic Model Lifecycle
The full lifecycle of a semantic model, from auto-generation through certification to ongoing maintenance.
Model generation below draws on the catalog, relationships, and metrics that Solid's offline process builds ahead of time — see Collect and Offline Process for how that foundation is produced.
Step-by-Step Lifecycle
AUTO: Model Generation
└─ Solid auto-generates: tables, columns, joins (incl. many-to-many),
metrics, fact/dim labels, PKs/FKs, descriptions for every entity
↓
HUMAN: Edit Models
└─ Modeler reviews and edits entities: corrects labels, adds context,
removes irrelevant columns — before the model can advance
↓
AUTO: Benchmark Question Generation
└─ Solid auto-generates test questions from SQL history; attaches
certified ground-truth SQL to each question
↓
HUMAN: Benchmark Review
└─ Modeler reviews all questions, adds new ones, removes irrelevant ones,
updates ground-truth SQLs — before running the test
↓
AUTO: Run Benchmark + Score + Root Cause
└─ Solid runs the benchmark, computes an accuracy score, identifies
root cause of each failed question
↓
HUMAN: Apply Fix Recommendations
└─ Modeler reviews each recommendation; applies or rejects.
Solid proposes an exact fix per failure (edit model or add instructions).
↓
HUMAN: Approve / Certify
└─ In Progress → Pending Review → Certified → Exposed to AI Agents
Only certified models are served to agents via MCP.
↓
AUTO: Automatic Updates
└─ Solid detects schema drift, new columns, changed joins; surfaces
targeted update recommendations. One-click apply.
↓
AUTO: Optimize from Real Usage
└─ MCP production usage patterns surface coverage gaps; Solid recommends
additions; modeler reviews and applies.
Approval Lifecycle States
| State | Meaning |
|---|---|
| In Progress | Model created; modeler is editing |
| Pending Review | Submitted for approval; awaiting certification |
| Certified | Approved and active; served to AI agents via MCP |
| Exposed to AI Agents | Only certified models are served; uncertified models are invisible to MCP |
The Human-in-the-Loop Principle
Every automated action Solid takes requires explicit modeler review before it takes effect. Solid does not silently update a model. This applies at three points in the lifecycle:
- Model generation — the modeler reviews and edits generated entities before advancing
- Benchmark questions — the modeler reviews, adds, and edits before running tests
- Automatic recommendations — the modeler explicitly approves or rejects each recommendation before any change is applied
Updated about 3 hours ago
Did this page help you?
