For journalists · source dossier
Not a newsroom, and not a press release. Primary sources, operational definitions of every quotable term, and a plain statement of what we are and are not claiming, so a story about us can be accurate.
Stage, stated plainly
Triodian is an early-stage company with a strong thesis and, as yet, no independently produced validation. Everything below is sourced to a primary document or labelled as first-party. Where a term is quotable but hard to falsify, we define it operationally and link the evidence.
What the company is
Triodian builds a governance layer that sits at the point an AI recommendation becomes an action, checks it against a policy the deploying institution authored, and produces a record an outside party can verify. Two enforcement configurations rest on established method and are deployable today; one signal is under open experiment, and is labelled that way wherever it appears. The company is early-stage: the thesis is strong, independent validation is not yet produced.
Fast facts
Base: Brisbane, Australia
Data residency: Australian residency available; deployment inside the customer boundary
Regulatory relevance: APRA CPS 234, CPS 230; EU AI Act; NIST AI RMF; ISO/IEC 42001
Stage: pre-launch; one production engine in an unrelated domain (pinpole)
Primary-source library
US 19/440,660 (USPTO Track One, filed 6 Jan 2026) and the CIP family, numbers and status.
The Deterministic Governance Architecture, the six-stage enforcement datapath.
The open Universal Governance Protocol and its conformance suites.
The claim-status register and the harness result set, first-party, graded.
Eight named tests, pre-registered floors, pass/fail criteria.
Operational definitions of every quotable term, each with its adversary.
Methods
Each definition names the adversary it addresses and links to its row in the claim-status register. The eight rules are surfaced in full on the Provable AI page rather than rewritten here.
The moment an AI recommendation crosses into an action that can't be taken back. Adversary: a decision that is irreversible before any human sees it. Register →
A distribution-free ceiling, certified at a stated confidence on a named corpus, on how often a violation gets through a detector. Adversary: a tuned threshold that looks good only on the data it was fit to. Method →
A set-level move of a decision stream out of a declared appetite, invisible to any single-decision check. Adversary: local compliance masking global drift. Method →
The property that every meaningful action path passes through the governed boundary. Adversary: an alternate route around the boundary. Method →
A fixed-order hardware datapath where stages 2–6 cannot be reordered or suppressed by software; stage 1 is the probabilistic input the rest narrows. Adversary: privileged software owning the enforcement host. Method →
Mode A governs what an action means (semantic); Mode B makes a forbidden output structurally impossible. Adversary: form-compliant, intent-violating output (A); an unemittable command being emitted (B). Method →
The eight conditions of verifiable responsible operation at the action boundary, defined in full, with their deliberate exclusions, on the Provable AI page.
For fact-checking
The same register the Evidence Centre carries: one row per claim, its status, its adversary, and what independent proof would look like. Nothing on it is graded above what we can support.
Open the register →What we are not claiming
People & credentials
Foundation chair, characterise exactly
Professor Toby Walsh (UNSW) has agreed to serve as independent chair, taking up the role on the Foundation's establishment. He leads the guardian, not the company, and must not be presented as endorsing any unvalidated technical claim.
The full team, with roles and prior programmes, is on the About page. When citing a person, distinguish their status: advisor/board (a governance relationship), cited (their published work is referenced), and quoted (they have given a statement for attribution). Do not collapse these.
Category of risk
The risk Triodian addresses is consequential AI actions taken without a tamper-evident record, faster than human oversight can intervene. Independent reporting on autonomous-agent incidents and the regulatory response (EU AI Act Article 6; NIST AI RMF; ISO/IEC standards) describe the category. We cite these as context for the class of risk, never as events we predicted, prevented, or were involved in.
Any incident we mention elsewhere on the site is cited as reported by others, for illustration of the category only.
Corrections
If we state something inaccurately, we fix it here and say what changed. The log is empty today, its presence is the commitment.
Corrections log · no entries yet
Media contact
Damian Hickey · damian.hickey@triodian.com
Media enquiries receive a substantive reply, not a call-booking link, within two business days. Embargo terms are agreed in advance for any pre-briefed material.
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