Who They Are
ANDEKS™ is stewarded by **Andrey Ekhmenin**.
The registered architecture identifies ANDEKS™ as an independent governance assessment system intended for organizations and decision-makers that need a bounded and attributable assessment of a specifically identified AI model, version, or distinguishable configuration before relying on broader governance, assurance, regulatory, or operational conclusions.
The TA-14 Registry presently records Andrey Ekhmenin as the steward of ANDEKS™ version 0.1. No organization is separately declared in the Registry baseline.
What They Are Building
ANDEKS™ is building a governance assessment architecture centered on **bounded object identity, declared assessment scope, evidence, and attributable findings**.
Its model requires the object being assessed to remain specifically identified rather than allowing a finding about one version, configuration, deployment, or evidentiary state to silently expand into a broader claim about an entire model family, provider, platform, or operational environment.
The architecture also preserves versioned normative baselines so changes to ANDEKS™ itself can be distinguished from earlier released states.
This makes ANDEKS™ primarily an **assessment-governance architecture**, not an execution-governance system.
What They Declared
In its registered declaration, ANDEKS™ states that it provides a normative framework for independent assessment of a specifically identified AI model, version, or distinguishable configuration against explicitly declared properties, claims, conditions of use, boundaries, and available evidence.
The registered architecture requires both the assessed object and the subject of assessment to remain explicitly identified and bounded. Findings are constrained to the fixed object, declared subject, applied conditions, and evidentiary basis used during the assessment.
ANDEKS™ also declares versioned normative baselines and attributable release lineage.
Its registered non-claims are equally important. ANDEKS™ does not claim to certify, license, accredit, approve, or authorize an AI system or organization. It does not establish legal or regulatory compliance, provide a universal model-safety determination, govern runtime execution, make deployment decisions, or transfer downstream responsibility to the assessor or to ANDEKS™.
Explicit Boundaries & Non-Claims
Publication of this profile does not constitute TA-14 certification, endorsement, accreditation, approval, legal validation, regulatory conformity assessment, technical-performance validation, ownership adjudication, or authorization for deployment or execution. TA-14 does not represent ANDEKS™ as a runtime execution-governance architecture, and no interoperability, partnership, certification relationship, or comparative superiority is implied by registration or publication.
Known Limitations
No additional public commentary is published for this section yet.
TA-14 Institutional Commentary
ANDEKS™ matters because it treats the **boundary of an assessment itself as a governance problem**.
An AI governance finding is only as trustworthy as the identity of the object examined, the evidence admitted, the conditions applied, and the limits placed on the resulting conclusion. When those elements drift, a bounded assessment can become an unbounded claim.
ANDEKS™ addresses that risk by preserving a distinguishable assessed object, explicit assessment subject, evidentiary basis, conditions, limitations, and version lineage.
From the TA-14 institutional perspective, that makes ANDEKS™ a useful example of an architecture occupying a distinct governance layer: **independent assessment before broader reliance**, while expressly declining to treat assessment as certification, authorization, regulatory approval, or execution governance.