Use cases

Real problems. Provable decisions.

PRAMETRA supports consequential decision contexts where evidence, authority, challenge, assurance, accountability and outcomes matter.

These are public decision-context models, not customer stories or claims of deployed production capability.

Assurance lensEvidence · Authority · Challenge · Assurance · Accountability · Outcomes

Decision contexts

Examine the decision, not just the feature list.

Each use case is framed through the same six assurance questions so the basis, authority and consequence of action remain visible.

01First proof domain

A bounded first proof domain for examining AI-supported operational decisions.

Decision challenge: Determine an appropriate response or escalation without collapsing context into a single recommendation.
Evidence: Relevant customer, policy and operational evidence must remain attributable and distinguishable from inference.
Authority: Delegated limits define who or what may recommend, approve and act.
Challenge: Conflicting signals and alternative interpretations remain visible for examination.
Assurance: The level of review should be proportionate to customer and operational consequence.
Outcome: The actual result can be verified and used to improve later decisions.

Decision contexts shaped by authority, policy, evidence and consequential risk.

Decision challenge: Assess a consequential recommendation within policy, risk and delegated-authority boundaries.
Evidence: Sources, assumptions and material contradictions remain traceable.
Authority: Capability does not replace the authority required to decide or approve.
Challenge: Recommendations can be tested against policy constraints and competing evidence.
Assurance: Higher-consequence decisions require stronger evidence and human control.
Outcome: Decision results remain available for accountable review and learning.

Human-governed decision contexts where evidence and accountability must remain visible.

Decision challenge: Support a decision without displacing professional responsibility or human accountability.
Evidence: Observed facts, source quality and model inference remain clearly separated.
Authority: Only appropriately authorised people and systems may progress the decision.
Challenge: Contradictions, uncertainty and missing evidence remain explicit.
Assurance: Review strength follows the potential consequence of error.
Outcome: Observed outcomes inform future assurance without rewriting prior evidence.

Decisions requiring explicit authority, traceability and public accountability.

Decision challenge: Evaluate a recommendation within policy, delegated authority and public-impact constraints.
Evidence: Material sources and reasoning inputs remain attributable for later review.
Authority: The mandate to recommend, approve or act is explicit and bounded.
Challenge: Affected assumptions and contradictory evidence can be examined.
Assurance: Oversight reflects consequence, policy and accountability requirements.
Outcome: The result can be reconstructed and assessed against the original intent.

High-consequence environments where assurance must be proportionate to impact.

Decision challenge: Determine whether a proposed action is sufficiently supported within defined control boundaries.
Evidence: Provenance and evidence integrity support reconstruction and examination.
Authority: Explicit permissions remain separate from technical capability.
Challenge: Material conclusions remain contestable before action.
Assurance: Approval and control intensity scale with decision consequence.
Outcome: Verification connects the decision record to what happened in practice.