In an era where nuclear energy is being called upon to meet global decarbonisation and reliability goals, the workforce behind it is being stretched thin. Between regulatory pressure, aging infrastructure, and increasingly complex documentation requirements, nuclear professionals spend a growing portion of their day on paperwork – not engineering.
Nuclearn is aiming to change that by harnessing the power of AI.
Founded by Brad Fox and Jerrold Vincent, Nuclearn was created because the pair were exhausted by inefficiency within the nuclear industry. With its private, secure AI solutions designed to accelerate documentation, streamline compliance, and increase engineering capacity. The platform, which they say is grounded in plant reality rather than Silicon Valley theory, has already been deployed across more than 50 facilities in the US, Canada, and the UK. NEi spoke with Brad and Jerrold to talk about what they’re building, why it matters now, and how AI can make nuclear power more effective, not just more efficient.
NEi: Let’s start with the big picture – what problem is Nuclearn solving in nuclear today?
Brad Fox, CEO & Co-Founder: It really starts with the people. Nuclear was never supposed to be this bloated from a staffing standpoint. Go back to the 1950s and 1960s, those early plant designers were imagining that these facilities could be run with 300 or 400 people. But today, many sites are staffing 700 to 800 or more per reactor.
And the problem isn’t safety or operations. The bloat is in documentation, compliance, procedure writing, and administrative burden. That’s the hidden cost of nuclear power. You’re paying highly trained engineers and operators to do manual, repetitive tasks that are necessary but slow and frustrating.
We founded Nuclearn because we were living through that friction. We believed there had to be a better way and AI, properly applied, offered the answer.
NEi: So this came from your personal experience inside the plants?
Jerrold Vincent, CFO & Co-Founder: Absolutely. Brad and I both spent years in nuclear operations. We were on the floor. We wrote the reports, sat through the reviews, got the same procedure kicked back five times because a citation was one character off.
It became obvious that most of the work we were doing wasn’t technical, it was matching patterns. It was compliance logic. That’s where AI shines.
We started small: document automation, CAP screening, repetitive risk assessments. But as we built trust and capability, the demand grew. Now, Nuclearn’s platform supports use cases across maintenance, safety, engineering, and regulatory functions.
NEi: What does the platform actually do – and how is it deployed?
Fox: At its core, Nuclearn is a private AI ecosystem that connects natural language processing with plant-specific data, processes, and security models. Our customers use it to:
- Write and validate procedures
- Analyze safety observations
- Classify work for capital vs. expense
- Perform document-based research across licensing and QA archives
- Assist with outage prep and planning, and more
It’s available as a private, on-premise system or a secure hosted model, built with compliance in mind. Everything is permission-based and auditable. The data stays private, and every customer environment is isolated.
NEi: How does Nuclearn ensure it’s “nuclear-grade” when it comes to AI?
Vincent: What we’ve built isn’t a generic AI model, it’s a platform trained on nuclear data, regulatory structures, procedural formats, and real-world use cases. Our AI doesn’t hallucinate because it’s grounded in context. If you’re pulling up a licensing document or CAP history, the system isn’t guessing, it’s searching verified documents in your environment and surfacing real excerpts.
We’ve also built in what we call “human-centered workflows.” That means the AI isn’t replacing the expert; it’s partnering with them. You’re always in control, verifying the output, editing as needed, and reviewing before submission.
NEi: You’ve mentioned the concept of an AI marketplace for nuclear. What does that look like?
Fox: That’s where it gets exciting. Right now, every plant is solving its own problems in isolation. A utility in Georgia may have built a brilliant AI-based outage prep tool, but no one in Illinois knows about it. What we’re building is a secure, nuclear-specific AI marketplace where utilities can share, buy, or adopt pre-trained models, prompts, and apps. It’s a way to accelerate innovation across the industry while respecting IP and data privacy.
The marketplace also supports community-driven learning. As more plants use similar tools, we can build in best practices and improve the model quality over time.
It’s open innovation, but within a secure, nuclear-compliant framework.
NEi: Let’s talk about your work beyond the US
Fox: Right now, most of our deployments are US-based, but that’s changing quickly. We’ve had strong traction in Canada with CNSC-regulated sites, and we’re starting to engage customers in the UK as well.
The beauty of our system is that it’s customisable. Even if the base AI was initially trained on US regulations, our clients can input their own documents – regulatory guides, site manuals, licensing histories – and the AI can search and reference those sources. So even before we’ve fully trained an international model, the system is still delivering value.
Vincent: And we’re working on that now. One of our goals for the next year is to build a more comprehensive international model. That means incorporating UK ONR standards, Canadian licensing terms, and other country-specific guidance into the core AI engine.
We’ve already laid the foundation with our architecture. Now it’s about scaling that intelligently.
NEi: How do you address the perception that AI is risky in high-consequence environments like nuclear?
Vincent: It’s a legitimate concern, and it’s why we’ve built Nuclearn to support – not replace – human judgment. We always say: in nuclear power, the operator is the hero. The engineer is the expert. Our platform exists to support them, giving them back time, reducing cognitive load, and letting them focus on the things that actually require human insight. Unlike many AI tools, ours is not a black box. Everything the AI produces is traceable. You can click and see where it pulled that citation from, what revision it used, and how it matched the prompt.
Fox: That’s why we’ve gained trust quickly. Our early adopters didn’t just see a flashy demo, they got results. Fewer documentation errors. Faster turnarounds. Higher compliance confidence. When you show up with a secure, auditable, proven solution that saves people hours a week, the scepticism fades.
NEi: Are there some real use examples?
Fox: A few stand out. One team reduced their procedure prep time by 50% using our AI assistant. Another used our capital vs. expense classifier to improve how work was coded, which had a material impact on their income statement.
We’ve seen safety analysts go from spending hours compiling observation trends to having a dashboard ready in minutes. Maintenance planners are using the system to streamline outage scope planning. It’s widespread.
Vincent: And those are just the formal use cases. Informally, we hear things like: “It helps me get unstuck.” Or “It makes me feel more confident that I haven’t missed something.”
That’s when you know the AI is doing its job, it’s reducing friction and building trust.
NEi: Where do you see the role of AI in nuclear heading over the next five years?
Vincent: We believe AI will become as essential as the control room. Not because it runs the plant, but because it frees the people who do. You’ll see AI embedded into safety analysis, license renewal planning, outage coordination, even vendor audits. Not to replace experts, but to make their expertise go further. That’s critical, especially as we face workforce attrition and an aging knowledge base. More importantly, we’re listening. Every feature we’ve built has come from a conversation with a utility, an operator, or an engineer who said, “What if it could do this?” That’s what keeps us essential, not just being smart, but being in service to the mission of
nuclear.
Fox: I think the bigger picture is: if we want to scale nuclear, we have to scale the human element too. We can’t just build more plants, we need to operate them with smarter processes, tighter workflows, and better use of our people’s time.
AI done right is how we get there. As the nuclear sector contends with aging plants, workforce turnover, and the need to scale new generation, the team at Nuclearn aims to set a new standard, not just for what AI can do, but for how it should be done. If AI is to play a role in the future of energy, it will need to earn the trust of the most exacting industry on earth.
Read more: Nuclearn secures nuclear AI funding
