Source
Record origin, ownership context, submission route, time and identifiers.
Decision trust · Decision provenance
Make the basis of a decision visible.
Decision provenance creates a traceable record of the evidence, analysis, assumptions, review and human judgement behind a consequential decision.
Traceable evidenceExplainable processHuman accountability
The proposition
A decision is more trustworthy when its journey can be reviewed.
Organisations increasingly make decisions using digital evidence, data, automated analysis and AI-assisted recommendations. The final outcome alone does not show whether the process was sound.
Trixure’s decision-provenance concept structures the record around what was received, what changed, what analysis was performed, what limitations were known, who reviewed the material and who made the final decision.
Core principle: provenance supports assessment and accountability. It does not prove authenticity, replace professional judgement or turn an analytical output into an automatic verdict.
Provenance chain
From source material to accountable outcome.
Integrity
Track versions, custody events, handling actions and material changes.
Findings
Retain methods, outputs, confidence, assumptions and known limitations.
Oversight
Document human review, challenge, exceptions and approval authority.
Rationale
Connect the outcome to the evidence considered and reasons recorded.
What the record contains
A structured evidence layer—not a black box.
The model is designed to preserve the context needed for audit, review, appeal, assurance and continuous improvement.
Material and lineage
Source references, timestamps, hashes or integrity markers, versions, custody events and relationships between original and derived material.
Methods and limitations
Tools, model or rule versions, analytical runs, findings, confidence indicators, assumptions, anomalies and unresolved questions.
Review and rationale
People and roles involved, evidence considered, challenges raised, overrides, approvals, final rationale and review status.
Trust controls
Designed for governed, reviewable use.
01
Versioned records
Preserve changes across evidence, analytical runs, findings and reports instead of overwriting history.
02
Role-based access
Separate submitters, analysts, reviewers, decision-makers and administrators according to responsibility.
03
Tenant and case separation
Maintain controlled organisational boundaries with scoped workspaces and evidence access.
04
Controlled reporting
Generate reviewable reports that identify evidence basis, methods, findings, limitations and approvals.
05
Human checkpoints
Require accountable review where automated analysis informs a consequential outcome.
06
API-ready architecture
Support controlled submission status and report retrieval as the capability matures—without exposing sensitive evidence by default.
What it can support
- Explain how a decision was reached
- Connect evidence to findings and outcomes
- Strengthen review, audit and appeal readiness
- Expose uncertainty and unresolved limitations
- Improve governance of AI-assisted workflows
What it does not claim
- It does not prove that material is authentic
- It does not provide a universal deepfake verdict
- It does not replace a judge, investigator or specialist
- It does not guarantee that a decision is correct
- It does not train on customer evidence by default
Potential applications
One provenance model, adapted to governed domains.
Evidence-informed decisions
Link evidential material, analytical findings, review and formal decision rationale.
Complex claims review
Preserve the basis of fraud indicators, specialist review, exceptions and outcomes.
Administrative accountability
Record data, policy, recommendations and approvals behind public-sector decisions.
AI-assisted operations
Govern consequential recommendations with traceable inputs, oversight and escalation.
Architecture and validation
Explore a governed decision-provenance use case.
Trixure is developing this capability through structured problem definition, architecture and controlled validation.
Discuss a Use Case