Every Arrival is
a Recognition.
A doorbell that doesn’t just ring — it understands presence. Harnessing deep-entry vision and architectural light to redefine how your home greets the world.
Your door
learns who
belongs.
Using our proprietary Presence-Flow™ algorithm, doorbellmart identifies the gait, facial structure, and proximity patterns of residents. It doesn’t just notify you; it prepares the home for your specific arrival sequence.
99.8%
Precision Acc.< 0.2s
Identity LatencyWELCOME HOME, ALEX
Intelligent entry systems, redesigned.
doorbellmart transforms passive entry points into adaptive intelligence layers that learn, predict, and respond to human presence in real time.
Adaptive Recognition
Continuously learns individual movement signatures such as gait rhythm, posture shifts, and approach speed to improve recognition accuracy without manual calibration.
Predictive Entry
Anticipates user arrival based on historical patterns and real-time proximity data, preparing door state, lighting, and internal environment before arrival.
Zero-Interaction Access
Enables seamless entry without keys, phones, or voice input by verifying identity passively through multi-sensor fusion.
Behavioral Mapping
Builds a dynamic behavioral model over time, tracking habitual entry times, dwell duration, and micro-interactions with the environment.
Environmental Sync
Automatically adjusts lighting, temperature, and ambient settings based on the recognized identity and contextual time of day.
Edge Privacy Processing
All biometric and motion data is processed locally on-device, ensuring sensitive identity patterns never leave the hardware layer.
How it works
Sensing Layer
Multi-angle depth sensors capture motion signatures as you approach your home, analyzing spatial positioning, walking speed, and environmental context in real time. The system continuously refines input accuracy across varying lighting conditions, weather patterns, and partial occlusions such as walls, gates, or crowds.
Identity Mapping
Presence-Flow™ constructs a behavioral identity model using gait rhythm, posture micro-adjustments, stride length consistency, and long-term movement patterns. Each interaction contributes to a continuously evolving profile that improves recognition confidence without requiring manual setup, tagging, or biometric enrollment steps.
Environment Sync
Once identity confidence thresholds are met, the system synchronizes environmental controls including lighting intensity, temperature balance, sound ambiance, and access permissions. These adjustments occur pre-entry, ensuring the environment transitions smoothly before physical arrival is completed.
What users say
“It recognized me before I even reached the stairs. It’s unsettling… but brilliant.”
— MARCUS R.“My home literally adjusts lighting before I open the door. It feels like living in the future.”
— ALICIA K.“The latency is insane. It reacts faster than I can think.”
— DEVON L.Privacy by design
All biometric data is processed locally on-device with no dependency on external servers for identity inference. Facial structure, gait signatures, and behavioral movement patterns are never transmitted or stored in the cloud. Presence-Flow™ models are encrypted at rest and in transit, and are periodically regenerated to prevent long-term trace reconstruction or identity replay attacks.
Each recognition session is isolated using ephemeral computation layers that discard raw sensor input immediately after processing. This ensures that no persistent biometric history can be reconstructed, even in the event of system compromise.
- • On-device inference only (edge AI processing)
- • Ephemeral identity tokens that expire per session
- • No raw video, depth map, or audio storage
- • AES-256 encrypted model layers with rotation cycles
- • Localized behavioral learning without external sync
- • Automatic biometric noise injection for trace protection
Security architecture is designed to minimize data persistence while maintaining continuous usability. Even in offline mode, the system retains full recognition capability without exposing sensitive identity vectors.