Engineering
intelligent futures.

We design embedded systems, deploy Edge AI on microcontrollers, and ship AIoT products for industrial and healthcare innovators — from concept to scaled deployment.

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8
Service domains
AIoT
Specialization
ESP32 · STM32
Hardware stack
TinyML
On-device AI
ESP32/STM32/TensorFlow Lite/MQTT/Django/Flutter/Edge AI/TinyML/PCB Design/Predictive Maintenance/Healthcare IoT/Industrial Automation/ESP32/STM32/TensorFlow Lite/MQTT/Django/Flutter/Edge AI/TinyML/PCB Design/Predictive Maintenance/Healthcare IoT/Industrial Automation/
§ 02 — Capabilities

Full-stack engineering for connected intelligence.

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01

Embedded Systems Development

From silicon to system

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02

Edge AI & TinyML Solutions

Intelligence on a chip

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03

AIoT — AI of Things

Connected. Intelligent. Autonomous.

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04

Product Development & Prototyping

Idea to working prototype

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05

Cloud & Backend Development

Scalable systems for connected products

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06

Mobile & Web Applications

Control surfaces for smart devices

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07

Industrial Automation

Operational intelligence

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08

Healthcare Technology

Care, monitored intelligently

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§ 03 — TinyML Playground

See our Edge AI in action.

Toggle anomaly modes and change inputs on simulated STM32/ESP32 microcontrollers to see real-time inference on the edge.

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Model specifications
Latency
12 ms
RAM Usage
8.4 KB
Flash Footprint
24 KB
Accuracy
98.2%
Parameter Controls1800 RPM
Trigger Anomaly StateSimulate fault conditions
DEVICE_STATE:ONLINE
TARGET: ARM CORTEX-M4
CALIBRATING EDGE NODE...
ML InferenceBEARING_STABLE
CPU Load8.1%
Confidence97.8%
§ 04 — Why EdgeintelliTech

We sit at the intersection of embedded and AI.

Most teams do one well. We engineer the whole stack — silicon to cloud to dashboard — so your product ships faster, runs leaner, and learns over time.

  • 01

    Embedded + AI Expertise

    Firmware engineers and ML practitioners on the same team.

  • 02

    End-to-End Product Development

    Hardware, firmware, cloud, app — under one roof.

  • 03

    Industrial & Healthcare Focus

    Deep domain experience in regulated, mission-critical environments.

  • 04

    Rapid Prototyping Approach

    Working hardware in weeks, not quarters.

  • 05

    Scalable AIoT Solutions

    Architectures designed for thousands of devices from day one.

§ 05 — Strategy & Insights

Featured Strategy Articles.

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Edge AIJune 13, 2026

Choosing the Right Hardware for TinyML: ESP32 vs. STM32 vs. Nordic nRF52

Choosing the wrong microcontroller for your Edge AI product can delay shipping by months or drive unit costs to unsustainable levels. Here is a technical breakdown of the top 3 silicon choices.

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Edge AIJune 13, 2026

Porting Python ML Models to C++ for Embedded Microcontrollers

Most machine learning models are designed in Python using float32 operations. Learn the exact step-by-step pipeline to translate these prototypes into static C++ arrays.

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Edge AIJune 12, 2026

Why Cloud-Only AI is Failing Your Hardware Products

Discover why sending raw sensor streams to the cloud is unsustainable for modern hardware products, and how running deep learning inference locally on microcontrollers saves costs.

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AIoTJune 08, 2026

Architectural Blueprints for Enterprise AIoT

Discover how to design and build scalable, secure, and resilient Artificial Intelligence of Things (AIoT) systems incorporating stream processing and real-time operations dashboards.

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HealthcareJune 05, 2026

Scaling Patient Care Safely: AIoT in Medical Devices

Medical device manufacturers face high hurdles: data privacy (HIPAA) and life-critical latency. Learn how embedding machine learning classifiers directly on medical wearables solves these.

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IndustrialMay 28, 2026

Stopping Catastrophic Downtime: The ROI of Industrial AIoT

Discover how industrial operations leads are utilizing Edge AI vibration sensors to detect mechanical bearing anomalies 48 hours before failure, boosting OEE.

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