WISDOMTWIN / RESEARCH
Open research / Roman Bodnarchuk

Make the wait
for judgment measurable.

Working papers on how role-specific AI could reduce enterprise decision delays—and the controls and evidence needed to test that proposition.

The research collection

WT-WP-001
Version 1.0
2026-09-25
Technical whitepaper

Sovereign Judgment Twins

A reference architecture for governed enterprise decision support

Connects authorized evidence, expert-informed frameworks, human authority and durable decision records, with a synthetic walkthrough and comparative evaluation plan.

Proposed architecture · Not peer reviewed
WT-100-001
Version 2.0
2026-09-03
Conceptual framework

Judgment Latency in Regulated Enterprises

A Conceptual Framework and Research Agenda for Role-Specific AI Decision Support

Defines judgment latency, separates evidence from hypotheses, and proposes six falsifiable propositions for role-specific AI decision support.

Preprint · Not peer reviewed
WT-200-001
Version 1.0
2026-09-24
Control specification

The WisdomTwin Trust Layer

A Testable Control Specification for Role-Specific AI Decision Support

Specifies authorization, role succession, evidence provenance, voice-meeting boundaries, human confirmation and testable release controls.

Preprint · Not peer reviewed
WT-300-001
Version 1.0
2026-09-24
Evaluation protocol

Measuring Judgment Latency and Net Time Recovery

A Staged Pilot Protocol for Role-Specific AI Decision Support

Defines staged testing, readiness clocks, quality constraints and measurement of human effort including review, rework and operating burden.

Preprint · Not peer reviewed

Evidence before claims

Observed evidence, proposed designs and synthetic examples carry distinct labels. Product outcomes require measurement.

Human authority remains explicit

Source access, generated recommendations and permission to act are separate questions.

Open and versioned

Read complete manuscripts, download the files and reuse original text with attribution under CC BY 4.0.