Services — AI × Connected Hardware

AI × Connected Hardware

Extending intelligence to the physical world.

We focus on the intelligence layer of hardware — not the hardware itself. We help brands extend their physical products with connected capabilities, embedded AI logic, and cohesive cross-device experiences. We work on the software, data, and interaction layers that turn existing devices into intelligent, connected ecosystems.

What We Do04 Core Areas

Connected System Architecture

Design communication protocols, device–app synchronization flows, telemetry pipelines, and edge–cloud coordination that enable intelligent interactions across devices.

Embedded Intelligence & Signal Processing

Develop AI-driven logic for real-time decision-making: motor control algorithms, multi-signal interpretation, behavioral modeling, safety logic, context awareness, and more.

Companion App & Experience Design

Build interfaces, usage journeys, error-handling logic, and multi-device UX that define how people actually use the hardware in the real world.

Data Loop & Cloud Integration

Design data schemas, monitoring dashboards, analytics layers, and feedback loops that create a full device → data → insight → iteration cycle.

What We Deliver

From hardware intelligence blueprints to production-ready pilot kits.

01Connected Hardware Blueprint

Includes

Device / gateway / cloud architecture (protocols, data flow, state management)
End-to-end mapping: Sensor → Signal → Feature → AI Decision
Device lifecycle model (connection, activation, usage, maintenance, updates)
Smart scenario decomposition (notifications, linkage, automation)
Data loop design (collection, storage, cleaning, retraining)

Value

Clear blueprint from hardware to intelligent system, clarifying scalability and smart ROI.

02Embedded AI Logic & Decision Design

Includes

On-device LLM / small model inference (local/cloud hybrid)
State recognition, behavior prediction, multi-modal signal fusion
Decision trees, context triggers, fault tolerance & backup
Real-time vs delayed response dynamic strategy

Value

Enable hardware to understand → judge → act, creating true intelligent interactions.

03Multi-Signal Fusion & Control Strategy

Includes

Sensor signal modeling (noise filtering, feature extraction, anomaly detection)
Actuator control parameters (force, speed, rhythm, boundaries)
Multi-modal fusion (IMU, heart rate, audio, motor current, etc.)
User behavior learning & adaptive control

Value

Enhance device action and decision precision, making hardware more intuitive and safer.

04Mobile App UX & Backend Dashboard

Includes

Device connection flow (network config / Bluetooth / broadcast)
Real-time status panel (volume, battery, mode, AI feedback)
Command dispatch, scene linkage, usage journey optimization
Device events to user visualization mapping

Value

Let users see what the device is doing — improving transparency and trust.

05Device-App Communication Standard

Includes

Bidirectional communication protocol (commands / status codes / errors)
Third-party capability extension (open API / plugin mechanism)
Contract between AI service and device service (session / token / QoS)

Value

Scalable ecosystem capabilities, supporting future product lines or third-party integration.

06Testing & Validation Manual

Includes

Device stress testing (stability / offline / exception recovery)
Software-hardware co-debugging process (debug toolchain, data calibration)
High-frequency scenario coverage (home, outdoor, weak network, multi-user)
Reproducible test scripts and validation metrics

Value

Ensure intelligent capabilities run stably in real environments, not just in demos.

07Pilot Release Kit

Includes

Logging & monitoring system (device logs, cloud logs, unified exception tracking)
OTA strategy & A/B testing mechanism
Analytics dashboard (user behavior, activation funnel, AI hit rate)
Reusable PoC/pilot deployment template

Value

Enable pilot → validation → scaling to truly work.

Featured Case Studies

AI × hardware products we've designed and built.

Consumer IoT