From What to Why
The Sensor captures what happened. The Translator explains why it matters. Layer 2 of the 5-Layer Architecture transforms raw signals into structured meaning by classifying the intent and emotional valence behind every interaction. A click is not just a click - the Translator determines whether it signals accidental engagement, idle curiosity, active consideration, or purchase intent.
Intent Classification
The Translator classifies intent into five categories: transactional (intent to purchase or convert), informative (seeking information or comparing options), social (engaging for social connection rather than transaction), exploratory (browsing without specific intent), and comparative (actively comparing alternatives). Classification confidence runs at 0.94 - meaning 94% of interactions are correctly categorized. This classification flows into the Logic Engine where contextual weighting determines how each intent type influences downstream decisions.
Tonality Analysis
Beyond intent, the Translator detects emotional tonality across five dimensions: enthusiasm (genuine excitement or interest), skepticism (doubt, caution, or resistance), neutrality (neither positive nor negative engagement), sarcasm (surface positive with negative underlying meaning), and urgency (time-pressure or immediate-need signals). Tonality is not simple sentiment analysis (positive/negative). It captures psychological state, which is essential for Computational Empathy and the Psychographic Layer.
Cross-Modal Alignment
Video, text, and audio signals are aligned to a common semantic space. A user who watches a product video enthusiastically (detected through audio tonality and viewing duration) but writes a skeptical comment (detected through text analysis) generates a richer intent profile than either signal alone. The Translator fuses these modalities into a unified intent representation that flows into the DNA layer for vector encoding.
Real-Time Sentiment Flow
Sentiment and intent flow into the Logic Engine and Command Center in real time - not as batch reports but as continuous streams. This means Performance Forecasting can detect a shift in audience sentiment toward a campaign within minutes, not days. The Integrity Layer can identify inorganic engagement patterns (consistent positive sentiment without behavioral follow-through) in real time. Strategic Guidance can adjust recommendations based on evolving audience response.
Computational Empathy Input
The Translator's intent and tonality output feeds directly into the Psychographic Layer and Strategic Guidance module. This is where Computational Empathy begins - understanding not just what people did but what they believe, resist, and value. The structured intent from the Translator becomes the input for belief modeling and psychological fit computation. Without the Translator, the system would know what happened but not what it means.