Known
Supported by evidence within the stated authority, scope, and limits.
Investigation · Digital forensics · AI assurance
Evidence before
conclusion.
The Zemi Method is a versioned evidentiary methodology for turning contested claims, incomplete records, and tool-derived outputs into findings that can be tested, explained, and challenged.
Current published method: v1.1 · July 2026
A repeatable reporting discipline
From source material to a defensible finding.
Zemi does not replace forensic standards or domain procedures. It governs the reasoning that connects authority, evidence, analysis, human judgment, and reporting.
01Source materialRecords, artifacts, outputs
→
02ObservationWhat is directly seen
→
03Tested claimCorroborated and bounded
→
04FindingHuman-adjudicated
Assumed
Relied upon for a stated and limited purpose, but not directly established.
Undetermined
Not resolvable on the available evidence after proportionate inquiry.
Current publication package
Read the authoritative record.
Three documents form the recommended reading path. Earlier versions remain available for comparison and provenance.
01
Authoritative method · Version 1.1
The Zemi Method
Principles, lifecycle, classifications, reporting requirements, AI-role boundaries, and the defensibility check.
02
Foundations companion · Version 1.3
Foundations and Positioning
The method’s intellectual lineage, literature, limitations, and relationship to adjacent professional standards.
03
Worked example · Version 1.1
Vendor Deletion Certification
A synthetic application showing how Zemi handles authority, conflicting evidence, source limits, classification, and reporting.
Research under the Zemi Method
Focused methods for modern evidentiary problems.
These publications extend Zemi’s reasoning discipline into recurring AI-assurance and agentic-AI attribution problems. They remain separately versioned and preserve their own scope and validation status.
Working paper · Version 1.0
Artifact-to-Finding Promotion
When an AI output, score, log, or other artifact is treated as supporting more than it actually establishes.
Public-review methodology · Version 0.4
Human–Agent Attribution Discontinuity
A forensic and assurance methodology for determining how far evidence supports attribution of a consequential AI-agent action to a natural person.
Versioned by design
A methodology should leave its own evidence trail.
The canonical text, archival DOI, file hashes, revision history, and limitations remain visible so readers can identify exactly what they are relying on.
The Zemi ecosystem
One body of work. Three distinct roles.
Methodology and research
ZemiMethod.com
The canonical home of the Zemi Method, its companions, worked examples, related research, versions, and integrity records.
You are hereApplied professional practice
Zemi North
The professional practice connecting the methodology to digital forensics, investigation, cybersecurity, and AI assurance.
Visit ZemiNorth.com ↗Author and broader work
Kevin V. Watson
The author’s professional profile, publications, research interests, and wider body of work.
Visit KevinVWatson.com ↗