Knowledge Base
Learn how DecodeIQ measures semantic intelligence. Explore detailed guides for each metric, understand the algorithms, and interpret your scores.
Core Mechanisms
The engine and architecture powering DecodeIQ's semantic intelligence platform
Foundational Concepts
The strategic frameworks and architectural principles behind semantic intelligence
Semantic Content Architecture
Production-ReadyThe design of entity models, relationship schemas, and content topology for AI-retrievable knowledge
Semantic Content Engineering
Production-ReadyStructuring, tagging, and optimizing content for machine consumption and AI retrievability
Brand Voice Architecture
Production-ReadySystematic capture and encoding of positioning, tone, and messaging frameworks for consistent brand expression
Competitive Intelligence
Production-ReadyData-driven analysis of competitor positioning, weaknesses, and market opportunities from SERP-validated sources
Production-Ready Metrics
Available Today - Fully validated and ready for production use
Semantic Density
Production-ReadyHow we measure knowledge concentration that predicts AI retrievability
Contextual Coherence
Production-ReadyMeasuring content consistency and topical focus across semantic themes
Retrieval Confidence
Production-ReadyPredicting AI citation likelihood based on semantic structure quality
Validation Phase Metrics
Design Partner Phase (Jan-Apr 2026) - Advanced metrics being validated with early partners
DecodeScore
In ValidationTopic momentum scoring methodology that quantifies competitive opportunity
Friction Index
In ValidationCompetitor vulnerability quantification based on sentiment analysis
Brand Voice Consistency
In ValidationAutomated brand alignment validation for tone and messaging