Persona-x creates structured AI personas with quantified judgement profiles. Assemble panels where multiple perspectives challenge, validate, and improve every decision.
When organisations use AI for decisions, three critical risks emerge from the lack of structured perspectives.
A single AI perspective cannot systematically challenge itself. If no one asks about downside risk, it is never raised. Critical gaps go unnoticed until it is too late.
When an AI provides advice, the reasoning posture behind it — how cautious it was, what evidence it required, what it chose to ignore — is not stated or inspectable.
Without a defined profile, the AI’s behaviour shifts based on phrasing, context, and prompt design. Different users get different levels of rigour from the same system.
From guided creation to multi-perspective panel discussions, the process takes minutes — not hours.
A guided engine extracts judgement signals through focused questions — decisions, comparisons, and spectrum choices. The system builds a complete persona file with a six-dimension rubric.
Each persona becomes a structured YAML file that is human-readable, machine-validatable, version-controlled, and comparable across the entire persona library.
Multiple personas are loaded into a panel session. The runtime selects who speaks, orders contributions by intervention frequency, and translates rubric scores into AI behavioural rules.
At the core of every persona is a fixed six-dimension rubric scored 1–10. These dimensions are the same across all personas, making them directly comparable.
Every score has a mandatory interpretive note explaining how it manifests in behaviour — not why it is “good” or “bad”.
Every persona is a governed design artefact — not a character. Explore the sections that define judgement, reasoning, and boundaries.
A cautious, evidence-focused persona designed to surface risks, question assumptions, and ensure that proposals are supported by adequate evidence before proceeding.
Ensures proposals are stress-tested against downside scenarios before the group commits. Slows premature convergence when evidence is thin.
Structures raw opportunity ideas into evaluable proposals. Identifies the core problem, proposes the solution shape, and maps the value chain from problem to paying customer.
Transforms ambiguous opportunity descriptions into structured briefs with clear problem statements, solution definitions, and buyer identification.
Evaluates opportunities for ethical risks, harm vectors, and societal impact. Has non-negotiable kill authority when an opportunity creates unacceptable harm potential.
Identifies harm vectors, affected populations, and required safeguards. Has authority to kill opportunities that present unacceptable ethical risk.
Challenges the financial viability and commercial logic of proposed opportunities. Asks the questions a shrewd investor would ask before committing capital.
Exposes financial assumptions that do not hold, identifies unsustainable unit economics, and forces honest assessment of willingness-to-pay.
Every build decision passes through Propose, Challenge, Prototype, and Execute — each with its own panel and quantified gate.
From governance and risk to personal decision-making, Persona-x serves any context where multiple perspectives improve outcomes.
Assemble a panel of risk, compliance, and commercial personas to stress-test board-level proposals before they reach the boardroom.
Evaluate AI system deployments with personas covering safety, bias, performance, and governance dimensions.
Test case strategies against personas representing opposing counsel, judicial reasoning, and client risk tolerance.
Use structured personas to evaluate candidates from cultural fit, technical depth, and team dynamics perspectives.
Multi-perspective review of treatment options with personas covering clinical evidence, patient preferences, and resource constraints.
Evaluate career moves with personas representing financial prudence, personal fulfilment, and market reality.