A single refinery can carry thousands of sensors measuring temperature, pressure, velocity, and viscosity. According to Applied Computing, operators make decisions using less than 8% of what those sensors tell them.
The London startup has raised a $20m Series A to close that gap, led by engineering giant KBR with Databricks Ventures participating. Founded in 2023, it is building a foundation model for oil, gas, refining, and petrochemicals.
The problem is not collection, according to co-founder and chief executive Callum Adamson. Operators already gather the information.
They cannot combine sensor readings, engineering documentation, and the underlying physics and chemistry fast enough to predict anything useful from them.
The shape will be familiar: a foundation model trained on proprietary industrial data, with a large incumbent as both investor and route to market.
