Auracelle is a strategic cognition and governance stress-testing suite that evaluates whether governance controls survive real decision conditions — adversarial behavior, cross-stakeholder incentives, and cascading dependencies.
Each module addresses a distinct domain of governance failure — together they form a coherent analytical suite for institutional stress-testing.
AI governance policy stress-testing. Interrogates institutional coordination, adoption dynamics, legitimacy thresholds, and evidence standards under adversarial and multi-stakeholder conditions.
Cyber governance incident escalation and resilience stress-testing. Models cross-sector response, supply chain trust dependencies, and decision thresholds for emergency powers and disclosure obligations.
Assurance and standards resilience for high-risk domains — nuclear, biotech, space, and frontier AI. Evaluates verification regimes and confidence calibration under constrained information and institutional stress.
A clean architectural separation that satisfies grant funders and consulting clients simultaneously — without compromising either relationship.
Transparent, citable, academically rigorous — grounded in Auracelle AI Governance Labs research and UC Berkeley CLTC affiliation. This is the research instrument submitted to funding bodies.
Configured deployments of the same engine — tailored to client context under NDA. You are selling access and expertise, not the underlying IP.
"We keep the methodology and measurement framework open and auditable, while tailoring scenarios, data, and decision matrices to client context under NDA."
The E-AGPO-HT and E-AGSO-HT frameworks underpin all three Auracelle modules. Methodology documentation is available to verified institutional partners and research collaborators under NDA.
A multi-stratum wargaming intelligence framework designed to quantify governance coordination failure under adversarial conditions, cross-stakeholder incentive misalignment, and cascading institutional dependencies. Developed and owned by Auracelle AI Governance Labs.
A parallel multi-stratum framework adapted for assurance and standards verification in high-risk domains. Evaluates whether standards regimes maintain integrity under institutional stress, constrained information, and adversarial pressure in nuclear, biotech, space, and frontier AI contexts.
Full framework documentation, scoring constructs, and simulation parameters are available exclusively to institutional partners, grant-funded research collaborators, and verified consulting clients under executed non-disclosure agreements. Contact Auracelle AI Governance Labs to initiate access.
The suite supports three engagement modes — each drawing on the same proprietary framework, deployed to fit the context.
| Engagement Type | Module Alignment | Mode | What It Delivers |
|---|---|---|---|
| Policy Stress-Testing | Charlie Orion | Consulting | Structured scenario runs that surface governance failure modes before policy implementation |
| Cyber Resilience Assessment | Orion | Consulting | Cross-sector incident escalation modeling; supply chain trust and emergency powers thresholds |
| Assurance & Standards Verification | Lyra | Consulting | Evaluation of whether verification regimes hold under institutional stress and constrained information |
| Academic Research Collaboration | Suite-wide | Research | Joint scenario design, publishable failure mode catalogs, and AAR outputs under open methodology terms |
| Institutional Wargaming Facilitation | Charlie Orion | Research + Consulting | Facilitated multi-stakeholder wargaming sessions for defense, intelligence, and international organizations |
| Frontier AI Safety Research | Charlie Lyra | Research | Empirical governance stress-testing for AI safety assurance frameworks and high-risk domain standards |
Whether you're a research funder, institutional partner, or an organization navigating high-stakes policy decisions — Auracelle has a deployment mode for you.