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Emotional Intelligence Infrastructure for Embodied AI
The Emotional Layer
AI Has Been Missing
AI models provide intelligence. Nearu provides presence, empathy, and trust — the layer that turns AI agents into entities people actually bond with.
AI-agnostic
REST API + WebSocket
Happy · 0.85
Meet Nearu
2:14 · Nearu introduces herself
0:00
Click play to hear Nearu speak
The Problem
Intelligence Without a Soul
Is Just Data Processing
The robotics and AI industry is building brilliance. Nobody is building the emotional layer that makes it human.
Agents are brilliant but cold
Today's AI assistants can answer any question — but they can't read the room. They miss tone, emotion, and human context entirely.
No emotional continuity
Every session resets to zero. No memory of who you are, how you felt, or what matters to you. Engagement drops. Trust never forms.
The missing layer
LLMs provide raw intelligence. Hardware provides presence. But the emotional intelligence layer — empathy, personality, expression — doesn't exist yet.
Our Solution
Meet the
Soul Engine™
Nearu provides the emotional intelligence infrastructure layer that sits between humans and any intelligent system — giving AI agents the ability to recognize emotion, respond with empathy, develop unique personality over time, and build persistent, evolving relationships with the user.
01
Sensing
Vision · Audio · Touch · ToF proximity
02
NearuVibe™
Multi-Channel Emotion Recognition
03
Agentic Core
Memory · Identity · Personality Matrix
04
LLM (AI-Agnostic)
GPT · Claude · Gemini · Local / On-prem
05
Embodiment
Micro-expressions · Body language
Technology
NearuVibe™
Emotion Engine
The "limbic system" of the machine. NearuVibe™ intercepts audio and video signals before the LLM — reading human emotion in real time and converting it into an EQ signal that shapes how the agent responds.
Multi-Channel Emotion Recognition
Voice prosody — tone, pitch, volume, pace, tremor. It doesn't just hear "I'm fine" — it hears the tremble that means "I'm not."
Semantic Analysis
Emotional meaning behind the words. Sarcasm, masking, and contradiction between what's said and how it's said.
Facial Expression Recognition
Micro-expressions via lightweight VER model trained on AffectNet (~450K faces). Confidence-weighted fusion with voice channels.
POST /api/v1/analyze-emotion → response
EMOTION CHANNELS
Three Signals. Zero Guesswork.
Acoustic Channel
Prosody — tone, pitch, volume, pace, tremor
- Voice tremor detection
- Real-time pitch analysis
- 50–100ms latency per frame
ACOUSTIC · LIVE INPUT
AI-Agnostic
Works with Any LLM
Nearu treats the LLM as a swappable brain. Persona, memory, and emotional layer survive model swaps — no rewiring required.
GPT
OpenAI
Claude
Anthropic
Gemini
Google
Llama
Meta
DeepSeek
DeepSeek
Local / On-Prem
Air-gapped support
PLATFORM
See What Nearu Actually Looks Like
A complete emotional intelligence layer — from real-time conversation to deep video analysis. Built for developers, designed for humans.
Real-time · Live Session
Talk to Nearu. She reads the room.
As you speak, NearuVibe™ analyzes your voice, words, and expressions simultaneously. Three independent channels. One interpreted emotional state. Nearu responds with genuine empathy — not scripted replies.
- Emotion detected in ~1.6s — before the LLM responds
- Tone, Words, and Face shown independently in real time
- Conversation history and emotional context persist across sessions
Live Demo
The Difference Nearu Makes
Same user. Same words. Two completely different experiences. Press Play to see it unfold.
Agent AStandard Avatar
No emotion detection
Standard Agent
● No emotion detection
⏱ Emotional state: unknown
Detected emotion: —No confidence data
Agent BNEARU Soul Engine™
NearuVibe™ monitoring
Standard AgentNEARU
NearuVibe™ monitoring
⏱ Neutral (baseline)
NearuVibe™ monitoring all signals...
Detected emotion
—No confidence data
Select a scenario above, then play to see the difference between standard and NEARU-enhanced responses.
Use Cases
Built for Every AI
That Touches Humans
EdTech
Learning & Training
Reads frustration and confidence signals — not just clicks — to adapt instruction in the moment. A trainer that feels when you're lost.
↑ Retention · Adaptive pacing
CX / Support
Customer Experience
Maintains active social presence during processing. Fills the silence. Higher CSAT, fewer escalations, deeper trust.
↑ CSAT · ↓ Escalations
Healthcare
Mental Health & Care
EQ layer for remote diagnostic agents — detecting emotional distress and escalating to human care when needed.
Safer remote care · ↑ Patient trust
Sales & Marketing
Conversion & GTM
Reads buying intent and mirrors the emotional register of a skilled sales rep. Visitors engage longer because they feel genuinely met.
↑ Engagement · ↑ Conversion
Robotics
Companion Robotics
Persistent memory and evolving emotional model. The relationship compounds — building familiarity and trust that drives category loyalty.
Deeper attachment · ↑ Retention
Automotive
In-Car Voice Assistants
Emotion-aware voice AI for the cabin — detects driver stress, fatigue, or frustration and adapts suggestions. Keeps interactions calm and focused for safer driving.
↑ Driver focus · Safer interactions
WHERE WE'RE HEADED
From Tool to
Relationship
The evolution of AI isn't just technical — it's relational. Every generation has moved closer to something people can actually bond with.
2000s – 2010s
Intelligent Tool
- Rule-based responses
- Does what it's told
- No context, no memory
2020 – 2024
LLM Agent
- Generates language
- Solves tasks
- Stateless, no identity
2024 – 2030
Embodied Agent
- Physical presence
- Multimodal sensing
- Still cold, inconsistent
NOW →
Relational Machine
- Stable identity
- Emotional responsiveness
- Trust, retention, bonding
The shift from functional AI to relational AI is the defining product transition of this decade. Empathy is becoming the primary differentiator for user retention in AI.
Competitive Advantage
What Nobody Else Has
Emotion AI Engine
Emotion recognition across multiple channels that processes signals in real time.
AI-Agnostic
Works with any LLM — GPT, Claude, Gemini, local. Persona and emotional layer survive model swaps.
Persistent Memory
Identity and relationship history that carries across sessions. No more reset to zero.
Prosodic EQ
Voice prosody — pitch, pace, tremor — so the system hears how you feel, not just what you say.
3-Channel Fusion
Acoustic, semantic, and facial emotion fused with confidence weighting for higher accuracy.
Structured JSON Output
Clean API response with labels, confidence scores, trend, and evidence summary for every call.
THE TEAM
Built by People Who've Done This Before
FAQ
Frequently Asked Questions
How exactly do you detect emotion?
How many emotions does Nearu recognize?
What is the system latency?
How do you handle privacy and compliance?
How does Nearu integrate with existing AI agents?
What makes Nearu defensible against big AI companies?
What does the persistent personality layer do?
Get Involved
AI shouldn't feel like a tool.
It should feel like someone.
We're looking for design partners, robotics OEMs, and investors who believe the next frontier of AI is relational.