AI Governance
Where QUOKKA AI may use generative or model-assisted systems, and how customers should interpret those outputs.
AI-assisted workflows can accelerate delivery, research, classification, and content handling, but they are not a substitute for contractual review, legal advice, or production sign-off.
Last updated: August 20, 2026
Depending on the engagement, AI may be used for prototyping, internal drafting, workflow orchestration, support acceleration, summarisation, retrieval, or task automation.
The exact model stack and tooling footprint depends on project scope, customer requirements, deployment environment, and risk posture.
Model output can be incomplete, incorrect, stale, or overconfident. It should be treated as an operational input that may require validation, not as an unquestionable source of truth.
Customers remain responsible for approving production decisions, regulated workflows, and externally published content unless a signed agreement explicitly states otherwise.
When AI is materially involved in a delivered workflow, we aim to make the automation boundary understandable to operators, stakeholders, and reviewers.
That includes documenting human review expectations, failure modes, and the limits of what the system is designed to decide automatically.
