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A coalition patent pool
for AI safety inventors.

The Casuarina Foundation stewards a multi-contributor coalition of AI safety and AI governance patents under a single mission-locked architecture. The Coalition activates with one contributing member, the Triodian portfolio, and opens to additional inventors once an audited operating cycle is on the public record. The structure is identical for every contributor.

The Coalition Patents Programme

Our Mission

Making AI Governance
Structurally Enforceable

The Casuarina Foundation exists to ensure that the governance of artificial intelligence is enforced through verifiable architectural mechanisms, not voluntary commitments, corporate pledges, or software layers that can be patched away. We pursue this mission as the neutral steward of a coalition patent pool dedicated to AI safety and AI governance, constituted as an Australian Company Limited by Guarantee.

The Foundation holds Coalition Head Licences over the patent portfolios contributed by each coalition member and exercises a uniform substantive governance mandate over how that technology reaches the world. The Coalition activates with one member, the Triodian portfolio, under documented terms that every subsequent admitted member will execute. Additional inventors are admitted once the first audited operating cycle is on the public record. No founding seat. No senior partner. No portfolio with primacy.

Our role is to ensure that coalition-contributed AI safety technology remains available on fair, reasonable, and non-discriminatory terms to every nation, every institution, and every organisation that needs it. Permanently, and beyond the reach of any single commercial interest. The Foundation's Australian domicile reflects three considerations: distance from the political volatility of any single AI superpower, supervision by an independent statutory regulator, and credibility across jurisdictions for an internationally constituted board.

We advise governments, regulators, standards bodies, and international institutions on practical approaches to AI safety and AI governance, grounded not in aspiration, but in the architectural reality of what coalition-pool technology, both hardware-enforced and software-based, makes possible.

01

Steward the Coalition

Administer the Coalition Patents Programme as a multi-contributor pool, with identical terms for every admitted member and FRAND licensing across the entire pool.

02

Advise Governments

Provide expert guidance to legislative bodies, regulatory agencies, and international organisations on structurally enforceable AI governance frameworks.

03

Enable Compliance

Support the practical implementation of AI governance regulation, including the EU AI Act, through technology that converts probabilistic AI outputs into deterministic, auditable results.

The Problem

Software Guardrails Are Not Guardrails at All

Every existing AI governance mechanism operates in software. Software can be patched around, updated away, acquired and quietly dismantled. A governance layer implemented in the same medium as the system it governs is not a constraint. It is a suggestion.

The Software Problem

RLHF fine-tuning, constitutional AI, output filters, prompt guardrails, and policy layers all operate at the same privilege level as the system they are meant to constrain. A sufficiently capable or deliberately adversarial system can, in principle, circumvent any of them.

The TEE Gap

Trusted Execution Environments (Intel SGX, AMD SEV, ARM TrustZone) provide hardware-enforced memory isolation. But each requires a software instruction to invoke them. A misaligned or adversarial process can simply decline to execute the entry instruction. The hardware protection exists; the mandatory pathway into it does not.

The Regulatory Void

The EU AI Act established the world's most detailed binding AI governance legislation. Yet no commercially available technology exists that enables verifiable, hardware-level compliance for high-risk AI systems. Regulation without enforcement technology is aspiration without architecture.

The Determinism Challenge

Probabilistic AI outputs cannot be accepted in high-risk, high-value, and regulated use cases (medical diagnosis, financial compliance, autonomous systems, critical infrastructure) without a mechanism that converts those outputs to deterministic, auditable, and cryptographically attested results.

The EU AI Act & Beyond

The European Union's AI Act represents the most ambitious binding AI governance legislation enacted to date. It creates legal obligations for providers and deployers of high-risk AI systems, obligations that demand verifiable compliance, not self-attestation. Yet no commercially available governance technology exists that meets these requirements at the architectural level.

The Casuarina Foundation exists, in part, to close that gap. The patent portfolio we steward establishes a hardware-enforced governance architecture that produces cryptographic compliance tokens at the point of AI actuation, providing the verifiable, tamper-proof governance attestation that the EU AI Act and similar global regulations will increasingly require.

Founder

Why This Foundation Exists

Damian Hickey

Damian Hickey

Inventor of the Triodian AI Governance patent portfolio (Coalition Member 1). Founder of Casuarina Foundation Ltd. Architect of the Coalition Patents Programme and the Deterministic Governance Architecture.

Damian Hickey initiated the Casuarina Foundation after watching the world's leading AI model companies push AI safety down the priority list in favour of competitive speed to market. Despite an accelerating global conversation about AI risk, no viable technical solution had emerged that could enforce governance at a level the AI system itself could not override.

The EU AI Act created binding legal obligations for AI governance, but no technology existed to meet them. Governments were writing regulations with no enforcement architecture. Industry was offering voluntary commitments with no structural accountability. And the fundamental technical challenge, converting probabilistic AI outputs into deterministic, auditable, and compliant results suitable for high-risk and regulated use cases, remained entirely unaddressed.

Mr. Hickey's response was not a policy paper. It was a patent. Filed with the United States Patent and Trademark Office in January 2026, the Deterministic Governance Architecture establishes a hardware-enforced governance pathway that the AI system cannot bypass, suppress, or decline to invoke. Governance is triggered not by software decision, but by a dedicated hardware signal responding to the semantic state of the AI model itself.

He then established the Casuarina Foundation in Australia, deliberately structured from inception as a coalition steward rather than a single-portfolio mission entity, and constituted as a Company Limited by Guarantee. The Triodian portfolio enters as Coalition Member 1 under the Coalition Founder Undertaking Deed, the Coalition Head Licence, and the Master Licence Agreement, the same instruments every subsequent coalition member will execute. The choice was structural, not symbolic. A single-portfolio steward, however well-intentioned, can be perceived as serving one inventor's interests. A coalition steward administering identical terms to every contributor is structurally different.

The choice of jurisdiction was equally deliberate. An Australian mission entity is domiciled outside the political volatility of any single AI superpower, supervised by an independent Commonwealth statutory regulator, and reads as globally credible to non-US audiences. A separately-incorporated US 501(c)(3) sister affiliate operates alongside the Foundation to receive US-tax-deductible donations and run public-benefit grant programmes globally.

The Foundation is not a gesture toward responsible AI. It is the structural instrument through which AI safety and AI governance technology, contributed by Triodian and by every subsequent coalition member, whether hardware-enforced, software-based, or hybrid, is made permanently available as a public good.

Our Approach

Hardware Enforcement,
Not Good Intentions

The Triodian patent portfolio addresses the deepest structural weakness in every existing AI governance approach: the governance layer is implemented in the same medium as the system it governs. The architecture we steward eliminates that weakness at the hardware level.

The Deterministic Governance Architecture integrates multiple hardware subsystems in a fixed-sequence pipeline. Each stage must complete before the next can begin. No software instruction can skip a stage, reorder the sequence, or suppress the governance process. Governance is triggered by a dedicated hardware signal responding to the semantic state of the AI model, not by software decision, not by policy configuration, and not by any mechanism the AI system can decline to invoke.

The result is an AI governance mechanism with a property the field has long recognised as essential but never achieved: a constraint that the system cannot itself remove.

The architecture produces cryptographic compliance tokens that attest not merely to platform configuration, but to the complete governance execution, covering the output, the constraint lineage, and a Hardware Root of Trust signature. an AI deployer can now provide regulators, auditors, and counterparties with verifiable, tamper-proof evidence that a governed process was executed and completed before the AI system was permitted to act.

Converting Probabilistic to Deterministic

AI systems produce probabilistic outputs. Regulated use cases (medical, financial, legal, safety-critical) require deterministic, auditable results. The Triodian architecture provides the hardware-enforced governance pathway that enables this conversion: constraining probabilistic AI output within a governed execution domain, binding the result to its constraint lineage, and releasing it only through a cryptographic actuation gate that attests to the complete governance process.

This is not post-hoc compliance monitoring. It is governance at the point of actuation, the moment the AI system attempts to act on the world.