CamIn designs and architects real-world products that connect seamlessly to the cloud and leverage AI and machine learning to deliver smart, automated and predictive capabilities, from the sensor on the board to the model that makes sense of what it measures.
A design consultancy specialising in cloud-connected hardware, smart product design and applied AI/ML. Most companies that want a product to be intelligent have to assemble a hardware team, a firmware team, a cloud team and a data team, then hope the seams hold. CamIn takes the whole path.
What CamIn is hired forThe hard part of a connected product is rarely any one layer. It is that the layers have to agree. A sensor choice constrains what the firmware can measure, the firmware decides what the pipeline receives, and the pipeline decides whether a model can be trained on it at all. Get that sequence wrong and the data arrives in a shape nothing useful can be learned from.
CamIn designs and architects across the whole of it: sensing and electronics, embedded firmware, secure device-to-cloud infrastructure, and the machine-learning layer that turns what the hardware measures into something worth acting on.
That means the questions that decide whether a product can be intelligent get asked at the schematic stage rather than discovered eighteen months later, when the fleet is in the field and the data turns out not to contain the answer.
Built on over 42 years across semiconductors, instrumentation, control systems, telecommunications and industrial IoT.
Each one is useful alone. The reason to have them in one place is that they constrain each other, and somebody has to hold all three at once.
Leveraging AI/ML models to turn raw hardware and sensor data into predictive insights. Getting that data off a physical product and into the cloud intact is a specialism in its own right. Sampling rate, power budget, what the radio can afford to send, what the firmware has to decide for itself: those choices set the ceiling on what any model can later learn.
Architecting secure, scalable device-to-cloud data pipelines and seamless OTA frameworks, for new designs and for retrofitting equipment already in the field. The pipeline decides whether a fleet can be learned from or only watched: what is captured, how often, what context travels with it, and how long it is kept.
Proven experience across industrial IoT, automotive telematics and high-density audio wearables. In every one of them, system performance is decided by how the components interact, not by how good any single one of them is. Developing those components in isolation increases the risk of integration issues and poorer product performance.
Architected the hardware-to-cloud data infrastructure and machine-learning foundation for a real-time industrial dust extraction monitoring platform, in partnership with Meridian Controls, who bring the clean-air domain expertise and the installed base.
Whether it is a new design, an existing product that should be connected, or a pile of sensor data nobody has turned into anything useful yet, tell us a little about it and we'll come back to you within one working day.