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Rigetti Computing, Inc.

Rigetti builds quantum computers and sells access to them.

Rigetti Computing is a quantum computing company. It builds machines that use the strange rules of quantum physics to solve certain math problems far faster than regular computers. The company makes money in two main ways. First, it sells its quantum computers to governments and research labs. Second, it rents out time on its own machines through the cloud, so customers can run experiments without owning the hardware. Its main customers are national labs, universities, defense agencies, and a few big companies exploring chemistry and finance problems.

Think of it as a very early airplane company in the 1920s. The planes are expensive, few people know how to fly them, and nobody is sure which routes will matter. But if air travel becomes huge, the companies that built the first reliable planes and trained the first pilots will have a big head start. Rigetti is trying to be that early builder. It makes its own superconducting chips, which must be kept colder than deep space, and it writes the software that lets people program them. The bet is that quantum computers will eventually crack problems in drug discovery, battery materials, and cryptography that today's computers cannot touch.

The company is still small and loses money. Its revenue is tiny, mostly from research contracts and government deals, and it spends far more on building machines and paying engineers than it takes in. That is normal for a deep-tech company at this stage. Rigetti went public in 2022 by merging with a blank-check company, which gave it cash to keep building. It is headquartered in Berkeley, California. The big risks are simple: the technology may take many years to become commercially useful, larger rivals like IBM, Google, and Microsoft are spending far more, and the company may need to raise more money before it turns a profit. The big reward is that if quantum computing works, Rigetti could be one of a handful of companies that know how to build it.

Saved answer · last researched 13 Oct 2026