FeaturesMachine verification
The proof

The DDL ran on a real database before reaching you.

Every deliverable goes through automatic auditing before being saved. The DDL executes on a disposable PostgreSQL, business questions become queries with expected results, and the confidence seal declares the verified fraction.

The problem

Why this exists

How it works today

The architecture document arrives looking good and nobody knows whether the script runs. The error shows up at deployment, in the middle of the night, when the cost of going back is highest and the document’s author is no longer in the room.

How it works with EVODA

The script executes in a rolled-back transaction during the audit; the "DDL validated on PostgreSQL" seal only appears if it executed without error. The acceptance test proves the model answers the business questions, and the load proof compares target and measured by arithmetic.

How it works

Machine verification from the inside

1The seal

The verified fraction, with weight, score and reason.

The confidence seal is the fraction of available verifications that was actually performed, never a probability of being right. Each factor shows with weight and situation, and a factor that does not apply leaves the average instead of entering as zero.

A load proof that was not measured shows as not measured. "Nobody measured" is different from "measured and passed", and the seal does not let the two be confused.

2What actually runs

Verification that executes, not verification that is claimed.

The DDL executes on a disposable PostgreSQL, in a transaction rolled back at the end. The acceptance test turns each business requirement into a query with an expected result.

The execution prompt inherits all of it: it ships with the verification steps and the rollback written out, so whoever applies it can validate on their side too.

Under the hood

The verifications, one by one

What actually runs before a deliverable is saved.

ddlReal execution on a disposable PostgreSQL, inside a rolled-back transaction
acceptOne query per business requirement, with the expected result declared
loadA proof plan with synthetic data and numeric targets; the target-versus-measured comparison is arithmetic
sealA non-applicable factor leaves the average; an unmeasured factor shows as not measured

Start with the schema you already have

Paste the structure, get the most serious findings in about two minutes, and decide later whether an engagement is worth opening. No account, no card.