Keigen Evidence Methodology
The operational discipline of producing evidence designed to support external review, applied selectively to commercial decisions where commercial, operational, contractual, or compliance stakes warrant it. The methodology operates through the Attention Monetary System (AMS) framework’s five layers — Intent, Attention, Trust, Policy, Governance — and graduates across three evidence levels. Its working test is short enough to quote: if a result matters commercially, operationally, contractually, or for compliance, someone must be able to show what happened, who acted, under what rules, and what evidence can support review.
Why the term exists
Most commercial activity in 2026 produces records — analytics events, CRM entries, payment confirmations, audit logs, agent identity tokens. These records establish that activity occurred. They do not establish whether the activity meets the standard required for the decision that follows.
A campaign attribution dashboard records 47 new customers without testing whether they were real, eligible, intended new customers. An AI agent’s API call is logged distinctly from the user’s action, without testing whether what the agent did matches what the user actually wanted. A prize-draw winner is selected by a documented algorithm, without testing whether the rules were fixed and the inputs frozen before selection.
The Keigen Evidence Methodology exists to name the discipline that closes these gaps. The methodology is graduated — most commercial decisions do not need heavy evidence infrastructure, and applying it universally would degrade its commercial usefulness. It is reserved for decisions where downstream external review by a sponsor, regulator, auditor, customer, insurer, payment provider, or counterparty is predictable.
Keigen Technologies UK Limited operates the methodology across four product domains: B2B website behaviour and pre-form sales decisions (BuyerRecon), ecommerce campaigns and growth quality (RealBuyerGrowth), AI-assisted and offshore work evidence (TimeToPoint), and governed allocations and sponsor-funded activity (Fidcern Verified Draw). Each product is an AMS-level adapter — the same five-layer framework applied to a different commercial domain.
Adjacent terms
| Term | Brief definition | Relationship to Keigen Evidence Methodology |
|---|---|---|
| Attention Monetary System (AMS) | The architectural framework structuring the Keigen Evidence Methodology across five operating layers: Intent, Attention, Trust, Policy, Governance. | AMS is the technical architecture; Keigen Evidence Methodology is the human-readable name for the discipline AMS operates. The two terms describe the same body of work at different levels of abstraction. |
| Evidence infrastructure | The discipline and tooling that produces a defensible record of what happened, who acted, under what rules, and what evidence can support review. | The category Keigen operates within. Evidence infrastructure is the broader noun; Keigen Evidence Methodology is Keigen’s specific implementation of it. |
| Benevolent Holding Field (BHF) | The operating condition under which the AMS framework’s five layers produce useful output: a disciplined commitment that the evidence work serves the buyer’s defensibility, not the seller’s persuasion. | BHF is a posture, not a feature. Evidence infrastructure built to flatter rather than to support review imports false confidence into commercial decisions and is worse than no evidence infrastructure at all. |
| The graduation principle | The operational rule that evidence infrastructure is graduated, not universal: Level 1 (verifiable through normal business action), Level 2 (lightweight evidence controls for selective high-risk paths), Level 3 (full evidence pack with manifest, custody, and qualified timestamping). | The graduation principle is the methodology’s hard operational boundary. Decisions verifiable through normal business action receive Level 1 outputs; heavy evidence infrastructure is reserved for decisions where downstream external review is predictable. |
| AMS Evidence Pack | A structured Level 3 deliverable containing: canonical manifest (JSON Schema 2020-12), buyer-facing PDF, chain-of-custody log, qualified electronic timestamp evidence, QA results, methodology version, redaction log, and verifier readme. | The AMS Evidence Pack is the artifact produced at Level 3 of the graduation. Level 1 and Level 2 outputs are lighter — diagnostic reports and evidence add-ons rather than full packs. |
| Qualified electronic timestamp | A timestamp issued under UK eIDAS or EU eIDAS by a Qualified Trust Service Provider listed on the relevant trusted list, which binds date and time to data using a UTC-linked time source and the provider’s advanced electronic signature or seal. | Used at Level 3 of the methodology. Keigen procures qualified timestamps from EU-listed providers through API integration rather than holding that status itself, and records the trusted-list status of every timestamp at issuance. |
| Six topic pillars | The recurring topic structure organising the methodology’s commercial application: provenance/authenticity/attribution; buyer motion vs noisy identification; reported growth vs earned growth; evidence of work in human-AI systems; governed outcomes and defensible selection; assurance before compliance. | Each pillar maps to a Keigen product domain and to a specific commercial question that adjacent identity, attribution, or audit infrastructure does not — and structurally cannot — answer. |
| The 2027 compliance bridge | The strategic thesis that methods built in 2026 to produce decision-grade commercial evidence become 2027 compliance evidence as EU AI Act high-risk obligations, ISO/IEC 42001 certification programmes, and the UK AI Assurance Roadmap come into force. | Pillar 6 of the methodology. It frames evidence infrastructure as a forward-bridge between current commercial defensibility and near-term regulatory compliance, rather than as a retrospective compliance burden. |
What the Keigen Evidence Methodology is not
Three categorical exclusions matter for accurate scope.
The methodology is not a qualified trust service. Keigen does not currently hold UK or EU qualified trust service provider status. It integrates with qualified timestamps issued by listed providers but does not provide qualified trust services itself.
The methodology is not legal advice or forensic certification. Evidence packs produced under the methodology are decision-useful for commercial and early compliance contexts. They are not forensic evidence under ISO/IEC 27037 certification, and they do not constitute legal opinion. Where legal proceedings or formal forensic certification are anticipated, Keigen recommends engagement with appropriate legal counsel and accredited forensic specialists alongside the evidence pack.
The methodology is not employee surveillance, productivity monitoring, or worker tracking. The work-evidence pillar (Pillar 4) verifies deliverable evidence, AI-agent activity records, and approval chains — not keystrokes, screen captures, or worker-level activity trails.
The methodology is not “evidence for everything.” The graduation principle is the hard operational boundary. Applying Level 3 machinery universally would degrade the methodology’s commercial usefulness.
Standards integration
The Keigen Evidence Methodology is built against published standards rather than proprietary protocols. The methodology references and integrates with C2PA Content Credentials, NIST AI RMF Generative AI profile, ISO/IEC 27037, ISO/IEC 42001, EU AI Act Article 11 and Annex IV, JSON Schema 2020-12, RFC 3161 timestamp protocols, IETF RFC 9421 HTTP Message Signatures, OAuth 2.1, OpenID Connect, and the AI agent identity stack being standardised by the OpenID Foundation, NIST, and the major payment networks through 2026.
Where AI agent identity tools answer who acted at the request layer, the Keigen Evidence Methodology answers what happened, under what rules, and what evidence can support review at the verdict layer one structural step above. The two operate in complement, not in competition.