Research projects / AI assurance

Research profile

MissionSAFE

Task-specific safety and control assessment with critical failures kept visible.

A Archetypal AI research initiative

AI assurance

Task-specific safety and control assessment with critical failures kept visible.

MissionSAFE's research direction connects an organization's policies and applicable controls to reusable rules, benchmark cases, and evidence. It distinguishes a broad enterprise-program assessment from a system-level gate, so a critical failure cannot disappear inside an average score. The work investigates what each form of evidence actually establishes and how control coverage differs from demonstrated enforcement. Evaluation should include legitimate use, boundary cases, bypasses, uncertainty, and unsupported claims of compliance.

The research question

How can mission-specific evaluations reveal critical control failures without overstating coverage as safety or compliance?

Research workstreams

A question. A method. A test.

Workstream 01

Policy-to-control-to-rule lineage and applicability

Workstream 02

System-level gates and benchmark design

Workstream 03

Evidence grading, bypass testing, and measured coverage

Evidence priorities

Make progress measurable.

The initiative is framed around testable questions. Its research direction should be assessed against observed evidence and the limits of each experiment.

  • Critical failures kept visible at the system level
  • Legitimate use, boundary cases, bypasses, and uncertainty
  • Measured enforcement distinguished from control coverage

Research goals and proposed mechanisms are not established findings. Product-linked tracks describe the research behind a capability, rather than a claim that its hypotheses have been validated.

Associated company

Archetypal AI

Archetypal AI Research for emergent behavior and alignment; Guarded for operational governance, audit, compliance, and risk.

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