Quantum computers promise to do lots of things that classical computers can’t. But they face a big roadblock: instability. 

“If you look at classical computers, they are very stable. They will stay on for years as long as there is power,” says Vishal Chatrath, CEO and cofounder of Oxford-based startup QuantrolOx. 

Quantum computers, on the other hand, require constant manual tuning, which is time-consuming and difficult. As a result, they spend much more time being tuned than actually being used.

QuantrolOx wants to automate this process using machine learning. Its software monitors and adjusts dozens of different parameters every microsecond, which helps increase the useful time the computers are in operation. It runs on classical computers and is designed to scale along with quantum computers.

It’s just raised €10.5m from the European Innovation Council (EIC) — which says that the company is “of strategic importance for EU sovereignty in quantum computing” — and will use the cash to support the launch of its product in 2023.

Out of the total investment, €2.5m is grant money that the company will receive upfront, and €8m will be available to the startup in exchange for equity at a later date, and can be unlocked when it receives matching investments from other sources — EIC will match VC investment up to €8m, and that can be spread across several rounds. So if in the future QuantrolOx needed to raise €10m, it would only need to raise €5m from VCs, and that would be matched by €5m from the EIC — the remaining €3m can be accessed in the same way at a later date.

QuantrolOx raised £1.4m in a seed round led by Nielsen Ventures and Hoxton Ventures earlier this year and has 17 employees.

The current state of quantum computing

Quantum computing is now where classical computers were in the 60s and 70s, and countries around the world are racing to establish the standards that will be used as the quantum industry grows.

Today, working quantum computers have just over 100 qubits of processing power, but in the future they will have thousands and eventually even millions of qubits. Manual tuning just can’t scale to these numbers.

According to Chatrath, the EIC’s funding scheme fits well with the needs of deeptech companies, which usually find it harder to raise equity than startups in other tech sectors. Particularly in Europe, investors tend to be averse to investing first in deeptech startups — having matching funding available can make a risky deeptech startup more attractive.

“It is harder to attract capital for deeptech in Europe than in the US. Support like this from the EU is a great way to de-risk the investment,” Chatrath tells Sifted. 

Clara Rodríguez Fernández is Sifted’s deeptech reporter, based in Berlin. Follow her on LinkedIn here.

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