QBee was founded in 2017 to help industrial IoT companies managing their embedded Linux devices. Ensuring distributed Linux IoT devices are secure, updated, connected and remotely accessible is a challenge, especially when they are from different vendors, and when there is a mix of old legacy units with new ones. qbee.io is a unique platform that is vendor agnostic and does not require software development or containers, thus saving time and costs to IoT companies regarding internal software development and manual configurations. Our platform addresses many IoT verticals such as industry 4.0, smart cities, sensor networks, vending machines, measurement equipment, etc. We operate towards devices manufacturers and system/devices integrators or operators. QBee aims to improve the current existing minimal viable product. Besides monitoring metric data, configuration data, communication patterns, Linux system behaviour, etc, it was identified the need of an accurate anomaly detection feature. Thus, it is critical to our product to include intelligent algorithms to detect automatically anomalies and thus ensure a secure and efficient maintenance of the connected devices. QBee aims to develop this critical feature from scratch to be the first player in the market offering a reliable solution with low false positive detection rate. QBee does not possess in-house expertise in machine learning for time series or unstructured data analysis, that is essential for this project. We are looking to recruit an Innovation Associate with the required skill set, in order to complement our team. The SME Innovation Associate programme is thus necessary for QBee to initiate R&D activities with a view to positioning QBee as a top player in large scale management of IoT devices. Acquiring these skills is thus fundamental for QBee to keep and extend its competitive advantage over the coming years and will allow QBee to outgrow into a forefront innovation player at global scale.
Project leader: Carsten Lehbrink
Institution: QBEE AS
Address: Nordre Follo