Service Overview

In-Cabin AI Agent

AI-powered Digital Cockpit service that transforms in-vehicle interactions through AI-driven voice recognition and automation. Enables hands-free control of navigation, climate, and entertainment — without relying on cameras. Integrates with existing IVI platforms to predict high-risk driving situations from CAN-bus data, delivering a safer and more personalized cabin experience.

Voice AIDigital CockpitIVIPrivacy-FirstCAN-busDriver MonitoringNLP

95%+

detection accuracy

98%+

voice recognition

<500ms

response latency

99.5%

system uptime

ASIL B/C

safety certified

Capabilities

Key capabilities

Driver Attention Monitoring

Real-time tracking of driver attention levels, fatigue detection, and alertness assessment.

Occupant & Gesture Recognition

Automatic detection of occupants, seat occupancy, and gesture-based vehicle control.

Natural Language Voice Commands

Context-aware voice assistant that understands driver intent and controls vehicle functions.

Personalized User Profiles

System learns individual driver preferences and auto-adjusts climate, seat position, and entertainment.

Safety-Critical Design

ASIL-compliant system design meeting automotive industry safety standards.

Technology

Technology stack

Component Technology
Monitoring Computer Vision, Deep Learning
Voice Processing NLP, Speech Recognition
Integration IVI Platform, Cluster, HUD
Personalization Machine Learning
Safety ASIL B/C Compliance

How we work

Implementation approach

1

Phase 1: Requirements & Integration Planning

  • Define cockpit integration requirements
  • Analyze existing IVI/Cluster/HUD systems
  • Plan DMS/OMS sensor placement and calibration
2

Phase 2: System Development

  • Develop driver monitoring algorithms
  • Train occupant detection models
  • Build voice assistant with automotive context
3

Phase 3: Integration & Validation

  • Integrate with vehicle cockpit systems
  • Conduct safety-critical testing (ASIL compliance)
  • Validate across different driver profiles
4

Phase 4: Deployment & Optimization

  • Deploy to vehicle fleet
  • Collect user feedback and performance data
  • Continuously improve based on real-world usage

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