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Edge Devices & AI/ML Integration for Real-Time Intelligence

We design, optimize, and deploy AI and ML models directly on edge devices, from NVIDIA Jetson and ARM Cortex to microcontrollers, enabling real-time inference, on-device intelligence, and cloud-edge orchestration at minimal latency.

When latency matters in milliseconds, connectivity is unreliable, or sending raw data to the cloud creates privacy and bandwidth problems; you need intelligence on the device itself. Waiting for the cloud is not a viable architecture when the decision has to happen at the sensor, the camera, or the machine.

Solution Section Background

Edge AI & ML Integration Services

Edge AI Architecture & Consulting icon

Edge AI Architecture & Consulting

We assess your hardware environment, use case requirements, and latency constraints to design an edge AI architecture that fits your devices, your data, and your operational reality before any model development or deployment begins.

AI Model Optimization for Edge Hardware icon

AI Model Optimization for Edge Hardware

We apply quantization, pruning, knowledge distillation, and neural architecture search to reduce model size and compute requirements, achieving INT8 and FP16 inference performance that runs reliably within your edge hardware memory and power envelope.

On-Device ML Inference Deployment icon

On-Device ML Inference Deployment

We package, convert, and deploy optimized ML models directly onto edge devices using TensorRT, TensorFlow Lite, ONNX Runtime, and OpenVINO, with hardware-specific tuning that extracts maximum inference performance from every target platform.

TinyML for Microcontrollers & Sensors icon

TinyML for Microcontrollers & Sensors

We develop and deploy TinyML models on ARM Cortex-M, STM32, ESP32, and Nordic nRF devices that perform keyword detection, anomaly detection, and sensor classification at microwatt power levels without any cloud dependency.

Computer Vision at the Edge icon

Computer Vision at the Edge

We deploy real-time object detection, defect inspection, and activity recognition models on NVIDIA Jetson, Hailo-8, and Intel Movidius platforms using YOLO, DeepStream, and MediaPipe pipelines optimized for on-device inference at production frame rates.

Edge MLOps & Model Lifecycle Management icon

Edge MLOps & Model Lifecycle Management

We build edge MLOps pipelines that manage model versioning, OTA updates, performance monitoring, and drift detection across deployed device fleets using AWS IoT Greengrass, Azure IoT Edge, Balena, and Mender.io so every device stays accurate and current.

Cloud-Edge Integration & Orchestration icon

Cloud-Edge Integration & Orchestration

We design cloud-edge orchestration architectures using MQTT, OPC-UA, AWS IoT Core, and Azure IoT Hub that synchronize on-device inference results with cloud analytics platforms, enabling hybrid intelligence that runs locally but learns globally.

Secure Edge AI Deployment icon

Secure Edge AI Deployment

We implement hardware-rooted security across edge AI deployments using secure boot, TPM attestation, OP-TEE trusted execution environments, OTA signing, and encrypted model storage so your AI assets and device fleet are protected from tampering and extraction.

Industries We Serve

We deploy edge AI across industries where real-time on-device intelligence directly determines operational safety, quality, and efficiency outcomes.

Manufacturing

Manufacturing

We deploy edge AI for real-time defect detection, predictive maintenance, and quality inspection directly on production line hardware, reducing defect escape rates and cutting unplanned downtime without cloud connectivity dependency.

We deploy edge AI for real-time defect detection, predictive maintenance, and quality inspection directly on production line hardware, reducing defect escape rates and cutting unplanned downtime without cloud connectivity dependency.

Healthcare

Healthcare

We integrate AI inference on medical edge devices for patient monitoring, diagnostic imaging support, and anomaly detection, meeting HIPAA privacy requirements by keeping sensitive clinical data processed locally rather than transmitted to the cloud.

We integrate AI inference on medical edge devices for patient monitoring, diagnostic imaging support, and anomaly detection, meeting HIPAA privacy requirements by keeping sensitive clinical data processed locally rather than transmitted to the cloud.

Retail

Retail

We deploy computer vision and behavior analytics models at the edge for shelf monitoring, customer flow analysis, and checkout automation, enabling real-time store intelligence without the latency or bandwidth cost of cloud-dependent video analytics.

We deploy computer vision and behavior analytics models at the edge for shelf monitoring, customer flow analysis, and checkout automation, enabling real-time store intelligence without the latency or bandwidth cost of cloud-dependent video analytics.

Construction

Construction

We deploy edge AI on construction site cameras and safety devices for real-time PPE compliance detection, hazard identification, and machinery proximity alerts, operating reliably in environments where network connectivity is inconsistent or unavailable.

We deploy edge AI on construction site cameras and safety devices for real-time PPE compliance detection, hazard identification, and machinery proximity alerts, operating reliably in environments where network connectivity is inconsistent or unavailable.

Manufacturing
Manufacturing

We deploy edge AI for real-time defect detection, predictive maintenance, and quality inspection directly on production line hardware, reducing defect escape rates and cutting unplanned downtime without cloud connectivity dependency.

We deploy edge AI for real-time defect detection, predictive maintenance, and quality inspection directly on production line hardware, reducing defect escape rates and cutting unplanned downtime without cloud connectivity dependency.

Healthcare
Healthcare

We integrate AI inference on medical edge devices for patient monitoring, diagnostic imaging support, and anomaly detection, meeting HIPAA privacy requirements by keeping sensitive clinical data processed locally rather than transmitted to the cloud.

We integrate AI inference on medical edge devices for patient monitoring, diagnostic imaging support, and anomaly detection, meeting HIPAA privacy requirements by keeping sensitive clinical data processed locally rather than transmitted to the cloud.

Retail
Retail

We deploy computer vision and behavior analytics models at the edge for shelf monitoring, customer flow analysis, and checkout automation, enabling real-time store intelligence without the latency or bandwidth cost of cloud-dependent video analytics.

We deploy computer vision and behavior analytics models at the edge for shelf monitoring, customer flow analysis, and checkout automation, enabling real-time store intelligence without the latency or bandwidth cost of cloud-dependent video analytics.

Construction
Construction

We deploy edge AI on construction site cameras and safety devices for real-time PPE compliance detection, hazard identification, and machinery proximity alerts, operating reliably in environments where network connectivity is inconsistent or unavailable.

We deploy edge AI on construction site cameras and safety devices for real-time PPE compliance detection, hazard identification, and machinery proximity alerts, operating reliably in environments where network connectivity is inconsistent or unavailable.

Our Edge AI Integration Approach

We follow a five-phase approach that moves from hardware assessment through to fleet-scale deployment, ensuring every edge AI system is validated on real hardware before it reaches production.

Hardware & Use Case Assessment-icon

01 Hardware & Use Case Assessment

We evaluate your target hardware specifications, inference requirements, power constraints, and connectivity environment to define a realistic edge AI deployment strategy that fits your devices and delivers the latency and accuracy your use case demands.

Model Selection & Optimization-icon

02 Model Selection & Optimization

We select or develop the right model architecture for your use case and apply quantization, pruning, and compilation techniques to reduce model size and computational cost while preserving the accuracy required for reliable operation on your target hardware.

Edge Deployment & Integration-icon

03 Edge Deployment & Integration

We package and deploy optimized models onto your edge devices with hardware-specific runtime configuration, integrating inference outputs with your existing sensor pipelines, control systems, and local storage so the AI fits naturally into your operational workflow.

Cloud-Edge Orchestration Setup-icon

04 Cloud-Edge Orchestration Setup

We configure the cloud-edge communication layer that synchronizes model updates, aggregates inference telemetry, and manages device health reporting across your fleet, giving you central visibility and control without compromising on-device autonomy or latency.

Monitor, Update & Scale-icon

05 Monitor, Update & Scale

We deploy monitoring and OTA update pipelines that track model performance across every deployed device, detect accuracy drift, push validated model updates to the fleet, and scale the infrastructure as your device deployment grows from pilot to full production.

Hardware & Use Case Assessment-icon

Hardware & Use Case Assessment

We evaluate your target hardware specifications, inference requirements, power constraints, and connectivity environment to define a realistic edge AI deployment strategy that fits your devices and delivers the latency and accuracy your use case demands.

01

Hardware & Use Case Assessment

02

Model Selection & Optimization

03

Edge Deployment & Integration

04

Cloud-Edge Orchestration Setup

05

Monitor, Update & Scale

Your Devices Are Smarter Than You Think.

We help you deploy AI directly on your edge hardware so your systems can see, decide, and act in real time without waiting for the cloud.

Edge devices CTA Banner

Edge AI Technology Stack

We work across the full edge AI hardware and software stack, from silicon to MLOps, selecting the right tools for your target device and deployment environment.

Nvidia Jetson (Orin, Xavier)
Nvidia Jetson (Orin, Xavier)
Intel Movidius
Intel Movidius
Hailo-8
Hailo-8
Qualcomm AI100
Qualcomm AI100
Raspberry Pi
Raspberry Pi
BeagleBone
BeagleBone
Arduino Portenta
Arduino Portenta
ARM Cortex-M series
ARM Cortex-M series
STM32
STM32
Nordic nRF, ESP32
Nordic nRF, ESP32
ESP32
ESP32
Arduino
Arduino
TensorFlow Lite Micro
TensorFlow Lite Micro
Edge Impulse
Edge Impulse
ONNX Runtime
ONNX Runtime
Intel OpenVINO
Intel OpenVINO
TensorRT
TensorRT
Pytorch Mobile
Pytorch Mobile
CoreML
CoreML
MediaPipe
MediaPipe
Nvidia Jetson (Orin, Xavier)
Nvidia Jetson (Orin, Xavier)
Intel Movidius
Intel Movidius
Hailo-8
Hailo-8
Qualcomm AI100
Qualcomm AI100
Raspberry Pi
Raspberry Pi
BeagleBone
BeagleBone
Arduino Portenta
Arduino Portenta
ARM Cortex-M series
ARM Cortex-M series
STM32
STM32
Nordic nRF, ESP32
Nordic nRF, ESP32
ESP32
ESP32
Arduino
Arduino
TensorFlow Lite Micro
TensorFlow Lite Micro
Edge Impulse
Edge Impulse
ONNX Runtime
ONNX Runtime
Intel OpenVINO
Intel OpenVINO
TensorRT
TensorRT
Pytorch Mobile
Pytorch Mobile
CoreML
CoreML
MediaPipe
MediaPipe
Nvidia Jetson (Orin, Xavier)
Nvidia Jetson (Orin, Xavier)
Intel Movidius
Intel Movidius
Hailo-8
Hailo-8
Qualcomm AI100
Qualcomm AI100
Raspberry Pi
Raspberry Pi
BeagleBone
BeagleBone
Arduino Portenta
Arduino Portenta
ARM Cortex-M series
ARM Cortex-M series
STM32
STM32
Nordic nRF, ESP32
Nordic nRF, ESP32
ESP32
ESP32
Arduino
Arduino
TensorFlow Lite Micro
TensorFlow Lite Micro
Edge Impulse
Edge Impulse
ONNX Runtime
ONNX Runtime
Intel OpenVINO
Intel OpenVINO
TensorRT
TensorRT
Pytorch Mobile
Pytorch Mobile
CoreML
CoreML
MediaPipe
MediaPipe
Nvidia Jetson (Orin, Xavier)
Nvidia Jetson (Orin, Xavier)
Intel Movidius
Intel Movidius
Hailo-8
Hailo-8
Qualcomm AI100
Qualcomm AI100
Raspberry Pi
Raspberry Pi
BeagleBone
BeagleBone
Arduino Portenta
Arduino Portenta
ARM Cortex-M series
ARM Cortex-M series
STM32
STM32
Nordic nRF, ESP32
Nordic nRF, ESP32
ESP32
ESP32
Arduino
Arduino
TensorFlow Lite Micro
TensorFlow Lite Micro
Edge Impulse
Edge Impulse
ONNX Runtime
ONNX Runtime
Intel OpenVINO
Intel OpenVINO
TensorRT
TensorRT
Pytorch Mobile
Pytorch Mobile
CoreML
CoreML
MediaPipe
MediaPipe
Nvidia Jetson (Orin, Xavier)
Nvidia Jetson (Orin, Xavier)
Intel Movidius
Intel Movidius
Hailo-8
Hailo-8
Qualcomm AI100
Qualcomm AI100
Raspberry Pi
Raspberry Pi
BeagleBone
BeagleBone
Arduino Portenta
Arduino Portenta
ARM Cortex-M series
ARM Cortex-M series
STM32
STM32
Nordic nRF, ESP32
Nordic nRF, ESP32
ESP32
ESP32
Arduino
Arduino
TensorFlow Lite Micro
TensorFlow Lite Micro
Edge Impulse
Edge Impulse
ONNX Runtime
ONNX Runtime
Intel OpenVINO
Intel OpenVINO
TensorRT
TensorRT
Pytorch Mobile
Pytorch Mobile
CoreML
CoreML
MediaPipe
MediaPipe
Nvidia Jetson (Orin, Xavier)
Nvidia Jetson (Orin, Xavier)
Intel Movidius
Intel Movidius
Hailo-8
Hailo-8
Qualcomm AI100
Qualcomm AI100
Raspberry Pi
Raspberry Pi
BeagleBone
BeagleBone
Arduino Portenta
Arduino Portenta
ARM Cortex-M series
ARM Cortex-M series
STM32
STM32
Nordic nRF, ESP32
Nordic nRF, ESP32
ESP32
ESP32
Arduino
Arduino
TensorFlow Lite Micro
TensorFlow Lite Micro
Edge Impulse
Edge Impulse
ONNX Runtime
ONNX Runtime
Intel OpenVINO
Intel OpenVINO
TensorRT
TensorRT
Pytorch Mobile
Pytorch Mobile
CoreML
CoreML
MediaPipe
MediaPipe
Nvidia Jetson (Orin, Xavier)
Nvidia Jetson (Orin, Xavier)
Intel Movidius
Intel Movidius
Hailo-8
Hailo-8
Qualcomm AI100
Qualcomm AI100
Raspberry Pi
Raspberry Pi
BeagleBone
BeagleBone
Arduino Portenta
Arduino Portenta
ARM Cortex-M series
ARM Cortex-M series
STM32
STM32
Nordic nRF, ESP32
Nordic nRF, ESP32
ESP32
ESP32
Arduino
Arduino
TensorFlow Lite Micro
TensorFlow Lite Micro
Edge Impulse
Edge Impulse
ONNX Runtime
ONNX Runtime
Intel OpenVINO
Intel OpenVINO
TensorRT
TensorRT
Pytorch Mobile
Pytorch Mobile
CoreML
CoreML
MediaPipe
MediaPipe
Quantization (INT8/FP16)
Quantization (INT8/FP16)
Pruning
Pruning
Knowledge Distillation
Knowledge Distillation
Neutral Architecture Search
Neutral Architecture Search
ONNX Conversation
ONNX Conversation
AWS IoT Greengrass
AWS IoT Greengrass
Azure IoT Edge
Azure IoT Edge
NVIDIA Fleet Command
NVIDIA Fleet Command
Balena
Balena
Mender.io
Mender.io
MLflow
MLflow
OpenCV
OpenCV
NVIDIA Omniverse Kit SDK
NVIDIA Omniverse Kit SDK
YOLO Ultralytics
YOLO Ultralytics
Roboflow
Roboflow
MQTT
MQTT
OPC UA
OPC UA
AWS IoT Core
AWS IoT Core
Azure Iot Hub
Azure Iot Hub
Google Cloud IoT
Google Cloud IoT
Secure Boot
Secure Boot
TPM
TPM
OP-TEE
OP-TEE
OTA Signing
OTA Signing
Hardware Attestation
Hardware Attestation
Encrypted Model Storage
Encrypted Model Storage
Quantization (INT8/FP16)
Quantization (INT8/FP16)
Pruning
Pruning
Knowledge Distillation
Knowledge Distillation
Neutral Architecture Search
Neutral Architecture Search
ONNX Conversation
ONNX Conversation
AWS IoT Greengrass
AWS IoT Greengrass
Azure IoT Edge
Azure IoT Edge
NVIDIA Fleet Command
NVIDIA Fleet Command
Balena
Balena
Mender.io
Mender.io
MLflow
MLflow
OpenCV
OpenCV
NVIDIA Omniverse Kit SDK
NVIDIA Omniverse Kit SDK
YOLO Ultralytics
YOLO Ultralytics
Roboflow
Roboflow
MQTT
MQTT
OPC UA
OPC UA
AWS IoT Core
AWS IoT Core
Azure Iot Hub
Azure Iot Hub
Google Cloud IoT
Google Cloud IoT
Secure Boot
Secure Boot
TPM
TPM
OP-TEE
OP-TEE
OTA Signing
OTA Signing
Hardware Attestation
Hardware Attestation
Encrypted Model Storage
Encrypted Model Storage
Quantization (INT8/FP16)
Quantization (INT8/FP16)
Pruning
Pruning
Knowledge Distillation
Knowledge Distillation
Neutral Architecture Search
Neutral Architecture Search
ONNX Conversation
ONNX Conversation
AWS IoT Greengrass
AWS IoT Greengrass
Azure IoT Edge
Azure IoT Edge
NVIDIA Fleet Command
NVIDIA Fleet Command
Balena
Balena
Mender.io
Mender.io
MLflow
MLflow
OpenCV
OpenCV
NVIDIA Omniverse Kit SDK
NVIDIA Omniverse Kit SDK
YOLO Ultralytics
YOLO Ultralytics
Roboflow
Roboflow
MQTT
MQTT
OPC UA
OPC UA
AWS IoT Core
AWS IoT Core
Azure Iot Hub
Azure Iot Hub
Google Cloud IoT
Google Cloud IoT
Secure Boot
Secure Boot
TPM
TPM
OP-TEE
OP-TEE
OTA Signing
OTA Signing
Hardware Attestation
Hardware Attestation
Encrypted Model Storage
Encrypted Model Storage
Quantization (INT8/FP16)
Quantization (INT8/FP16)
Pruning
Pruning
Knowledge Distillation
Knowledge Distillation
Neutral Architecture Search
Neutral Architecture Search
ONNX Conversation
ONNX Conversation
AWS IoT Greengrass
AWS IoT Greengrass
Azure IoT Edge
Azure IoT Edge
NVIDIA Fleet Command
NVIDIA Fleet Command
Balena
Balena
Mender.io
Mender.io
MLflow
MLflow
OpenCV
OpenCV
NVIDIA Omniverse Kit SDK
NVIDIA Omniverse Kit SDK
YOLO Ultralytics
YOLO Ultralytics
Roboflow
Roboflow
MQTT
MQTT
OPC UA
OPC UA
AWS IoT Core
AWS IoT Core
Azure Iot Hub
Azure Iot Hub
Google Cloud IoT
Google Cloud IoT
Secure Boot
Secure Boot
TPM
TPM
OP-TEE
OP-TEE
OTA Signing
OTA Signing
Hardware Attestation
Hardware Attestation
Encrypted Model Storage
Encrypted Model Storage
Quantization (INT8/FP16)
Quantization (INT8/FP16)
Pruning
Pruning
Knowledge Distillation
Knowledge Distillation
Neutral Architecture Search
Neutral Architecture Search
ONNX Conversation
ONNX Conversation
AWS IoT Greengrass
AWS IoT Greengrass
Azure IoT Edge
Azure IoT Edge
NVIDIA Fleet Command
NVIDIA Fleet Command
Balena
Balena
Mender.io
Mender.io
MLflow
MLflow
OpenCV
OpenCV
NVIDIA Omniverse Kit SDK
NVIDIA Omniverse Kit SDK
YOLO Ultralytics
YOLO Ultralytics
Roboflow
Roboflow
MQTT
MQTT
OPC UA
OPC UA
AWS IoT Core
AWS IoT Core
Azure Iot Hub
Azure Iot Hub
Google Cloud IoT
Google Cloud IoT
Secure Boot
Secure Boot
TPM
TPM
OP-TEE
OP-TEE
OTA Signing
OTA Signing
Hardware Attestation
Hardware Attestation
Encrypted Model Storage
Encrypted Model Storage
Quantization (INT8/FP16)
Quantization (INT8/FP16)
Pruning
Pruning
Knowledge Distillation
Knowledge Distillation
Neutral Architecture Search
Neutral Architecture Search
ONNX Conversation
ONNX Conversation
AWS IoT Greengrass
AWS IoT Greengrass
Azure IoT Edge
Azure IoT Edge
NVIDIA Fleet Command
NVIDIA Fleet Command
Balena
Balena
Mender.io
Mender.io
MLflow
MLflow
OpenCV
OpenCV
NVIDIA Omniverse Kit SDK
NVIDIA Omniverse Kit SDK
YOLO Ultralytics
YOLO Ultralytics
Roboflow
Roboflow
MQTT
MQTT
OPC UA
OPC UA
AWS IoT Core
AWS IoT Core
Azure Iot Hub
Azure Iot Hub
Google Cloud IoT
Google Cloud IoT
Secure Boot
Secure Boot
TPM
TPM
OP-TEE
OP-TEE
OTA Signing
OTA Signing
Hardware Attestation
Hardware Attestation
Encrypted Model Storage
Encrypted Model Storage
Quantization (INT8/FP16)
Quantization (INT8/FP16)
Pruning
Pruning
Knowledge Distillation
Knowledge Distillation
Neutral Architecture Search
Neutral Architecture Search
ONNX Conversation
ONNX Conversation
AWS IoT Greengrass
AWS IoT Greengrass
Azure IoT Edge
Azure IoT Edge
NVIDIA Fleet Command
NVIDIA Fleet Command
Balena
Balena
Mender.io
Mender.io
MLflow
MLflow
OpenCV
OpenCV
NVIDIA Omniverse Kit SDK
NVIDIA Omniverse Kit SDK
YOLO Ultralytics
YOLO Ultralytics
Roboflow
Roboflow
MQTT
MQTT
OPC UA
OPC UA
AWS IoT Core
AWS IoT Core
Azure Iot Hub
Azure Iot Hub
Google Cloud IoT
Google Cloud IoT
Secure Boot
Secure Boot
TPM
TPM
OP-TEE
OP-TEE
OTA Signing
OTA Signing
Hardware Attestation
Hardware Attestation
Encrypted Model Storage
Encrypted Model Storage

SuccessStories

Engineered Real-Time Appliances Health Monitoring System Through Embedded Edge Connectivity

Engineered Real-Time Appliances Health Monitoring System Through Embedded Edge Connectivity

Dynamisch developed a centralized telemetry platform that enables continuous monitoring of appliance performance across distributed device fleets. The solution delivered 65% faster issue detection, a 27% reduction in repair time, and a 34% increase in genuine spare part sales, while reducing annual platform maintenance costs.

Read Full Story
01 / 02

Why Choose Dynamisch

At Dynamisch, we engineer edge AI and ML integration across the full hardware spectrum, from ultra-low-power microcontrollers to real-time multi-model inference on NVIDIA Jetson platforms. Every solution includes the fleet management infrastructure to keep your deployed models accurate, updated, and performing reliably as you scale.

Full Hardware ,Spectrum Coverage-image

Full Hardware
Spectrum Coverage

TinyML to Full ,GPU Edge Inference-image

TinyML to Full
GPU Edge Inference

Edge MLOps & ,Fleet Management-image

Edge MLOps &
Fleet Management

Secure & Compliance-,Ready Deployments-image

Secure & Compliance-
Ready Deployments

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Frequently Asked Questions about Edge Devices & AI/ML Integration

Ready to Deploy Intelligence at the Edge?

From TinyML on microcontrollers to real-time inference on NVIDIA Jetson, we deploy AI on the hardware your operations actually run on.

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