Assessment
Assessment Development
Framework mapping, generated content, validation evidence and assurance workflows.
Open →Use Cases
Applications built on governed inference.
Interface can support many workflows because the underlying primitives are shared: assets, frameworks, inference runs, evaluations and reviews. The design principles apply everywhere — but each context brings different ones to the foreground.
Use cases
Each entry is a route into the same platform layer. The principle tags show where the design emphasis falls.
Education
Educational Assessment
Item generation, curriculum alignment, evaluation, auditability and assessment governance.
Open →Conversation
Conversational Analytics
Turn conversations into analysable behavioural and cognitive data.
Open →Development
Coaching & Development
Generate and evaluate coaching outputs, feedback, reports and development recommendations.
Open →Research
Human-AI Interaction Research
Study offloading, reasoning, cognitive acts and AI-mediated workflows.
Open →Knowledge
Knowledge Management
Process documents, notes, annotations and captures into reusable knowledge artefacts.
Open →Governance
AI Governance
Inference provenance, audit trails, review workflows and evaluation records.
Open →Learning
Organisational Learning
Understand how teams create, preserve and improve organisational knowledge.
Open →Contextual design
The same principles apply everywhere. Context determines which ones lead.
Context
Governed Inference
Contexts where the inference carries institutional weight — formal assessment, regulated decision-making, AI governance. The output will be defended, audited or acted upon by third parties. Speed and fluency matter less than defensibility and audit trail.
The design emphasis is on making the inferential argument explicit and traceable, and ensuring the organisation controls the infrastructure producing it.
Context
Augmented Practice
Contexts where AI extends what practitioners can do without substituting for what only practitioners can judge — coaching, organisational development, learning analytics, professional knowledge work. The question is always what the human can do with the machine, not instead of it.
The design emphasis is on keeping the human in the decision loop and making the AI-practitioner interface fit the workflow rather than demanding the workflow fit the tool.
Context
Knowledge Stewardship
Contexts where the data being processed is sensitive, longitudinal or strategically significant — conversations, documents, organisational knowledge records. The data is the asset; the platform is the tool. The key concern is whether the organisation retains control over what is inferred from it and where it goes.
The design emphasis is on ownership of derived outputs, portability of structured artefacts, and transparency about what was inferred from what.