Consulting
Clarify the decision with strategy, architecture and governance.
Explore consultingEnterprise AI value architecture
Make the AI decision. Before the implementation.
Know where AI belongs, what should change and what must remain human. Then decide what deserves to be built.
- No predetermined outcome
- Explicit decision boundaries
- Consulting · Products · Implementation
Three ways to work with Theory Y
Consulting first. Then a clear choice.
Products
Explore Teradius, our enterprise AI product with native agents and governed flows.
Explore productsImplementation
Discuss product implementation, integration or module licensing.
Explore implementationTheory Y Technologies owns Teradius and has a commercial interest in its adoption. We state our commercial interests at the start of every engagement. Our advice does not presume selection of any product or that Theory Y should deliver the next stage.
The question is not “Can we build it?”
What deserves to be built?
Value
Will this solve the right problem?
Test the opportunity against the current process, the cost of change and the outcomes that matter.
Readiness
Can the organisation support it?
Consider the systems, information, ownership and capability the proposed change needs.
Authority
Who decides when it matters?
Make human review, escalation and the consequence of a wrong decision part of the design.
These three questions are the dimensions of the AI readiness check
The flagship engagement
One review. A better basis to decide.
Executive AI Value Architecture Review
A focused engagement to examine the opportunity, the assumptions and the evidence needed to proceed.
- A clearly framed business decision
- A view of value, risk and readiness
- A recommendation with its reasoning
A paid advisory engagement.
Executive decision recordIllustrative
A recommendation. With its reasoning attached.
- The decision
- Should this workflow use AI?
- The boundary
- Defined process. Named owner. Human oversight.
- The evidence
- Value, readiness, risk and operating constraints.
Do not build a solution without a case.
The evidence does not justify further investment in this proposed use of AI, or the risks exceed the agreed boundary.
Next actionDocument the reasons and consider non-AI alternatives.
A worthwhile opportunity may not be ready.
A prerequisite is missing: data access, operating ownership, capacity or a dependency the organisation must resolve.
Next actionRecord the dependency, owner and condition that triggers reconsideration.
Resolve the uncertainty before investing.
A material assumption remains untested. Gather the missing evidence before making an implementation commitment.
Next actionDefine the evaluation question, representative cases and acceptance criteria.
Move forward within a defined boundary.
The agreed evidence supports a bounded next step, with named ownership and explicit operating controls.
Next actionConfirm the scope, approval authority and conditions for release.
Illustrative format. Not a client result, template promise or approved recommendation.
Product
Teradius
A standalone base for governed AI.
Teradius
A standalone base for governed AI, with optional modules and packs.
Pre-release. Early access by invitation.
Explore TeradiusA Theory Y module may be licensed for use within your solution, by arrangement and under agreed licence terms. Explore implementation
How work runs
One justified decision. Then the next.
Three stages form the consulting conversation.
- 01
Clarify the decision
The outputA decision frame and an agreed scope.
- 02
Examine the evidence
The outputA value, risk and readiness view.
- 03
Recommend the next step
The outputA recommendation, rationale and accountable next action.
04Architecture
Design the operating system.
Implementation05Delivery
Build a bounded increment.
Implementation06Operation
Measure, review and adapt.
ImplementationGrounded in recognised practice
Our method draws on government guidance and international standards. How we use them
- Australia’s AI Ethics Principles
- Voluntary AI Safety Standard
- ISO/IEC 42001:2023
- NIST AI Risk Management Framework
- Privacy Act 1988 and the APPs
- TOGAF Standard
Theory Y’s practical interpretation. Not certification, accreditation or legal advice.
Accountability is not an abstraction
AI assists. Responsibility stays human.
Our recommendations do not presume that AI is the answer, or that Theory Y should deliver the next stage.
What this means for governanceDirectly accountable.
Jerry Williams
Director, Theory Y Technologies Pty Ltd
Jerry leads the practice and the conversation with the organisation’s sponsor, connecting the business question to architecture, governance and delivery responsibilities.
Thinking before implementation
Start with a better question.
Is your organisation ready for AI, or just ready to buy it?
Assess readiness for a defined workflow, not for AI in the abstract.
AI can plan your outreach. Who approves what runs?
Let an assistant plan. Keep sign-off, caps and the record with your team.
Before you build or licence: five things to agree in writing.
Decide first. Then agree scope, data, ownership, hand-off and exit in writing, one bounded step at a time.
The next right decision
Your question. The conversation that fits.
Start with a review of the decision, talk about a product, or discuss implementation.