Dia · Oct 25, 2026
The readiness score tells you before anyone asks
Each database connection gets a readiness score from 0 to 100, calculated without AI. A sample CRM scored 24 of 100 with 3 of 152 tables approved. That is the point. You see what Dia can answer for before the business does.
- Readiness of a sales CRM before any modelling work
- 24 / 100
- Dia pull request #120
- Tables linked to an approved entity
- 3 of 152
- Dia pull request #120
- Joins approved
- 2 of 478
- Dia pull request #120
- Readiness unit tests passing
- 14
- Dia pull request #120
The problem
When an AI answers questions about a database, nobody can see how much of that database it understands. It sounds equally sure whether it knows three tables or three hundred.
Method
The score is calculated by code, with no AI involved. It adds up five parts:
| Part | Points | What it measures |
|---|---|---|
| Coverage | 25 | Tables linked to an approved entity. A proposed entity counts half. |
| Approval | 25 | Approved relationships, out of all known relationships. |
| Evidence | 20 | Measures with a stated level of detail, and relationships with evidence. |
| Knowledge | 15 | Curated questions, facts and abbreviations, relative to size. |
| Health | 15 | Errors and warnings per object, adjusted for how fresh the data is. |
A score of 70 or more is governed. From 40 to 69 is partial. Below 40 is raw.
Data
The same sample company data used for the planner. It is demo data. All 17 connections scored raw: sales CRM 24, accounts receivable 20, HR 11, Vision 11.
Results
The sample sales CRM scored 24. Coverage and approval added almost nothing: just 3 of 152 tables and 2 of 478 joins were approved, worth less than one point together. The 24 comes from evidence, knowledge and health.
The score shows exactly where work is missing. Approving entities and joins would raise it the most.