Control Rooms came to us with a thesis and a prototype — not a product.
Their bet: a self-training anomaly-detection algorithm, built for the complex, continuous data of industrial plants, has real value. They understood the data, the environment, and what they wanted out of the system.
Complexity
What they didn't yet have was the scale, the interface, and the workflow that would make it something a customer could actually deploy and adopt.
Approach
That's where we came in. We built the design framework and principles that developed hand in hand with their go-to-market strategy — a framework flexible enough to let the product take shape around real plants and real operators as the learning came in. Today Control Rooms is deployed across multiple plants and growing, on an architecture designed from the start to keep evolving.
Control Rooms went from an idea to a product deployed across multiple plants — and it's still growing.
