IoT and Embedded AI Systems
IoT and Embedded AI Systems combine connected devices, sensors, and embedded software to collect and exchange data in real time - enabling intelligent automation and monitoring across industries.
What are IoT systems used for?
IoT and Embedded AI systems are used to collect, process, and analyze data from connected devices such as sensors, machines etc.
In industrial environments, they are commonly used for monitoring equipment, tracking assets, optimizing production processes, and enabling real-time decision-making.
At xBerry, we build IoT solutions by integrating hardware, embedded software, and cloud infrastructure into a unified system. The process covers everything from device connectivity and data transmission to integration with existing platforms such as ERP or MES.
How do we build IoT systems?
We build IoT systems by integrating hardware, embedded software, and cloud infrastructure into a unified solution.
The process includes connecting devices and sensors, collecting and transmitting data, processing it in real time, and integrating it with existing systems such as ERP or analytics platforms.
Solutions are developed starting from an MVP and scaled into production-ready systems designed for reliability in real-world environments. We also handle device management, OTA updates, and long-term system maintenance to ensure security and stability over time. Real-world examples include Automatic Grinder, an automated grinding system with 0.2 mm accuracy, and RentingLock, a remote access control system for real estate using Bluetooth-connected electronic locks.
IoT Implementation Process
Discovery and solution architecture
We define business goals and use cases, and design the IoT architecture, including devices, connectivity, backend, and integrations.
Output: architecture tailored to the environment and requirements
Hardware and connectivity selection
We select sensors, edge devices, and communication technologies such as Wi-Fi, LTE, NB-IoT, or LoRaWAN, considering range, power consumption, and reliability.
Output: optimized hardware and connectivity stack.
Data collection and communication
We configure devices to collect and transmit data to IoT platforms or backend systems using protocols like MQTT, HTTP, or CoAP.
Output: secure and reliable data flow.
IoT platform and data processing
We implement an IoT platform (cloud or on-premise) to manage data, devices, and business logic, including alerts and automation.
Output: centralized data and device management system.
Integration with business systems
We integrate the IoT solution with existing systems such as ERP, MES, or custom applications via APIs and workflows.
Output: connected ecosystem and automated processes.
Device management and system maintenance
We monitor devices, perform OTA updates, manage security, and continuously optimize system performance.
Output: long-term reliability, security, and scalability.
Case study

Automatic Grinder
Automatic Grinder’s exceptional capabilities enable the automation of intricate grinding tasks, maintaining an astonishing accuracy level of up to 0.2 mm.

RentingLock
RentingLock is a system that enables remote access control for real estate via a multifunctional mobile app connected to electronic locks using Bluetooth.
