QuantrolOx is an Anglo-Finnish deep-tech startup, spun out of the University of Oxford in 2021 and now headquartered in Espoo, Finland. We build AI- and machine-learning-based control software that automatically tunes, stabilizes, and optimizes qubits, the fundamental building blocks of quantum computers. The problem: Unlike classical computers, which run reliably for years with no intervention, today's quantum computers require constant manual tuning by highly trained quantum physicists just to keep qubits calibrated. Qubits are extremely sensitive to noise and drift, and as systems scale from dozens of qubits to the hundreds of thousands or millions needed for useful computation, this manual tuning problem grows exponentially harder. As a result, quantum labs spend most of their time and expert talent maintaining hardware instead of running computations or advancing the science. Why it matters: This tuning bottleneck is one of the biggest practical barriers standing between today's experimental quantum computers and commercially useful machines. There simply aren't, and never will be, enough expert physicists to hand-tune millions of qubits one by one, so without automation the industry cannot scale. Our solution: QuantrolOx's software runs on classical hardware alongside the quantum system, continuously monitoring and adjusting many parameters in real time, on microsecond timescales. It is technology-agnostic and can be applied across different qubit platforms, though we have initially focused on solid-state qubits, where we've already demonstrated clear improvements in tuning speed and machine uptime. By automating this process, we free up scientists' time, increase the useful operating time of quantum computers, and remove a key bottleneck to scaling the entire field