SAFE-T — Structured AI Formalization & Enforcement Technology.
SAFE-T evaluates AI outputs before they are used in real workflows. It identifies issues, enforces validation conditions, and determines whether results are accepted, flagged, or rejected.
Validates before use.
SAFE-T reviews submitted output, detects issues that matter, and prevents unreliable or unverifiable results from moving forward into real workflows unchecked.
- Validation status such as validated, assumptions present, flagged, or rejected
- Violation register with specific findings
- Structured rewrite or corrective output when required
- Clear pass, revision, or rejection disposition
Control over output behavior.
Find material problems.
Surface assumption leakage, undefined validation logic, and unstable claims before they become operating issues.
Apply defined conditions.
Keep outputs inside explicit boundaries so results can be judged under repeatable rules rather than loose interpretation.
Accept, flag, or reject.
SAFE-T does not just comment on outputs. It determines whether they are allowed to pass.
SAFE-T is the operational validation surface.
Use the live interface to submit prompts, outputs, policies, or system descriptions for structured validation review.
Open the live protocol.
Go directly to the SAFE-T Protocol site to run evaluations and generate structured output records.