Author
Research Basis
Applied research supporting reliable AI-mediated communication.
My method draws on applied research into retrieval-supported communication, response stability, and interpretive drift. Metrics are used as calibration signals — not as guarantees of outcomes.
System View
The simplified system supporting responsible client communication.
Six connected layers — from the CRM system of record through QA calibration — form the operational backbone of reliable AI-mediated communication.
- Layer 01CRM
System of record for the client relationship.
- Layer 02Client Data
Structured records, statuses, and history.
- Layer 03Verified Knowledge Base
Approved, versioned answers and sources.
- Layer 04RAG Layer
Retrieval-supported response generation.
- Layer 05Communication Channels
Email, SMS, chat, and staff handoff.
- Layer 06QA Calibration
Stability, drift, and calibration monitoring.
This diagram is a simplified reference model. Actual implementations vary by organization, data structure, tooling, and operational context.
Behavioral Calibration Framework
Three behavioral evaluation metrics for AI-mediated communication.
RSI, IDS, and RCS are used together to assess and calibrate AI-supported responses against a verified knowledge base and defined communication policy.
RSI
Response Stability Index
Measures whether the same or rephrased question yields consistent, in-scope answers across repeated queries.
IDS
Interpretive Drift Score
Measures how far generated responses drift from the approved knowledge base and defined response boundaries.
RCS
Response Coherence / Structure Score
Measures structural coherence and alignment of tone, scope, refusal behavior, and escalation with the documented communication policy.
These metrics are used as internal calibration signals. They do not represent guaranteed performance and depend on the client's knowledge base, workflow scope, and operational context.
Publications
Peer-reviewed research and professional contributions.
Co-Author
Psychological Testing as an Instrument of Differentiated Support in Education, Healthcare Settings, and Crisis Life Transitions: Typological, Trait-Based, and Psychodynamic Approaches
Metaverse Science, Society and Law
DOI: 10.69635/mssl.2026.2.2.38 Additional research activities include participation in the “Beyond Human: AI, Consciousness, Personality and the Future of Human Development” international scientific conference (September 2026) as Conference Operations & Digital Workflow Coordinator.
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