# NuScale Power taps AI to speed up small modular reactor design after going public via SPAC > Source: > Published: 2026-08-30 20:12:44+00:00 # NuScale Power taps AI to speed up small modular reactor design after going public via SPAC The nuclear startup says AI-powered tools cut information retrieval times by 80%, a potentially significant edge in the race to deploy factory-built reactors. NuScale Power, the company behind the only small modular reactor design ever certified by the US Nuclear Regulatory Commission, is betting that artificial intelligence can shave years off the slow, document-heavy process of building nuclear plants. The company announced a partnership with Nuclearn and Nuclear Promise X (NPX) to develop AI tools tailored specifically for reactor engineering, licensing data, and internal knowledge management. Early proof-of-concept testing showed an 80% reduction in the time it takes engineers to retrieve critical information. In an industry where a single licensing review can consume millions of pages of documentation, that kind of efficiency gain is less “nice to have” and more “existential advantage.” ## What NuScale is actually building The partnership centers on Nuclearn’s AtomAssist platform, which runs on language models trained specifically on nuclear engineering data rather than the general-purpose large language models powering consumer chatbots. That distinction matters. General-purpose AI tools tend to hallucinate, which is a quirky feature when you’re writing a poem and a catastrophic liability when you’re designing a nuclear reactor. NuScale’s approach keeps all AI-generated outputs fully traceable to controlled documentation, meaning every answer the system produces can be traced back to a verified source document that meets regulatory standards. The practical goal is straightforward: help engineering teams scale their institutional knowledge without scaling their headcount at the same rate. Nuclear projects generate enormous volumes of proprietary data during design, licensing, and construction. Historically, navigating that data has been a bottleneck that slows down project execution and inflates costs. NuScale’s 77 MWe Power Modules are designed to be factory-built and shipped to site. The company’s VOYGR power plant design can scale up to 12 modules in a single installation, producing up to 924 MWe of electricity. ## Why timing matters The announcement lands at a moment when electricity demand is surging in ways the grid wasn’t designed to handle. Data centers powering AI workloads are driving an unprecedented spike in power consumption, and hyperscalers like Microsoft, Google, and Amazon have all signaled interest in nuclear energy as a reliable, carbon-free baseload source. NuScale trades on the NYSE under the ticker SMR. The company’s SPAC merger in 2022 gave it access to public capital markets. ## The broader AI-nuclear convergence What makes NuScale’s approach notable is the emphasis on nuclear-specific AI rather than off-the-shelf tools. The NRC requires exhaustive documentation trails, and any AI system used in reactor development needs to produce outputs that can withstand regulatory audit. Building on domain-specific language models trained on controlled nuclear data is a deliberate choice to meet that standard. The partnership with Nuclearn and NPX also reflects a broader pattern in the energy sector: smaller, specialized AI firms teaming up with domain-specific companies rather than competing with the foundation model giants. Nuclearn’s AtomAssist platform isn’t trying to be ChatGPT. It’s trying to be the only AI tool a nuclear engineer would trust with safety-critical information. The competitive landscape is also shifting. Companies like Kairos Power, X-energy, and TerraPower are all pursuing advanced reactor designs with varying degrees of government support and private funding. NuScale’s regulatory head start, being the only NRC-certified SMR design, is a meaningful moat, but moats erode if competitors move faster on deployment. **Disclosure:** This article was edited by Editorial Team. For more information on how we create and review content, see our [Editorial Policy](https://cryptobriefing.com/editorial-policy/).