How VERN Works

The Emotion Engine That Makes AI Feel Human

VERN is an Emotion Recognition System (ERS) that detects real human emotions—like anger, fear, joy, and sadness—in every sentence of a conversation. It’s what makes AI truly empathetic, responsive, and trusted.

🧩 Step 1: VERN Analyzes Each Sentence

As users speak or type, VERN breaks down each sentence in real time. It looks beyond keywords—analyzing linguistic structure, phrasing, intensity, and context to detect emotional cues.

Unlike sentiment analysis, VERN doesn’t guess how a person feels—it measures it.

🎯 Step 2: Emotion is Detected and Scored

For every sentence, VERN returns four emotional scores:

  • 🔴 Anger

  • 🔵 Sadness

  • 🟢 Fear

  • 🟡 Love/Joy

Each score is a number from 0 to 100. If a score is above 51, that emotion is significantly present. Multiple emotions can exist in the same sentence—and VERN tracks how they shift across a conversation.

📊 Step 3: Emotional Trends Over Time

VERN doesn’t just capture one moment—it watches how emotions build, shift, and resolve.

This allows:

  • Emotional escalation detection (e.g., frustration growing over time)

  • De-escalation tracking (e.g., calming a distressed user)

  • Empathy-based performance metrics (for bots, reps, or therapists)

🤖 Step 4: Real-Time Use in Your AI or System

VERN integrates into your product via API or on-premise model. The emotion data can be used to:

  • Adjust chatbot tone or response style

  • Trigger escalations or support workflows

  • Power emotionally aware avatars or voicebots

  • Feed into analytics dashboards for insights and reporting