As tech giants such as Meta, Google, and Microsoft have entered into cooperation agreements with nuclear power companies, the integration of artificial intelligence and the nuclear industry is accelerating. In this trend, the startup Nuclearn, which focuses on AI solutions for nuclear power plant operations, recently announced a $10.5 million Series A funding round led by Blue Bear Capital, with AZ-VC, Nucleation Capital, and SJF Ventures participating.

The company revealed that its AI tools are already in use at over 65 nuclear reactors worldwide, mainly to optimize business operations at nuclear power plants. Bradley Fox, co-founder and CEO of Nuclearn, said that although no one has proposed letting AI directly control nuclear reactors, power companies are showing increasing interest in using AI technology to improve operational efficiency.

Nuclearn was founded based on the work experiences of its two founders at the Palo Verde Nuclear Generating Station in Phoenix, Arizona. While working at the nuclear power plant, Fox and co-founder Jerald Vincent began experimenting with data science methods to simplify various repetitive tasks, gradually adopting more advanced AI models.

Money Capital Funding

These practices soon attracted attention from other nuclear power plants. Fox recalls that other reactor operators contacted them, asking if they could provide similar solutions for their plants. This demand coincided with the period of the COVID-19 pandemic, and the two founders decided to start this startup during their spare time.

In terms of technical implementation, Nuclearn has developed AI models specifically trained on nuclear industry terminology. The company can train customized models for utility companies and power suppliers that have specific needs. Although its software primarily runs in the cloud, if customers have special requirements for their security protocols, the company can also assist in deploying hardware equipment on-site.

Currently, Nuclearn's software is mainly used to generate routine documentation for nuclear power plants, which are then reviewed and signed by the plant staff. Fox explained that the nuclear regulatory commission currently views AI technology as a tool, similar to the use of Excel, Mathematica, or other engineering software, with the ultimate responsibility still resting with the relevant personnel.

To ensure safety, nuclear power plant operators can set threshold levels for automation based on their own comfort level and confidence in the model's processing capabilities. Fox said that when the AI model is uncertain or determines that human intervention is needed according to the set parameters, the system will send the task to the relevant personnel for secondary confirmation. He recommends that clients view this system as an auxiliary tool for junior employees.

From an industry development perspective, the nuclear industry's acceptance of AI technology reflects the trend of digital transformation in traditional energy industries. As the demand for stable power supply from tech companies increases, nuclear power, as a clean energy option that provides uninterrupted power 24 hours a day, is gaining more attention.

Nuclearn's business model reflects the characteristics of AI technology application in highly regulated industries. The company does not attempt to fully automate nuclear power plant operations but instead focuses on improving operational efficiency and reducing human error, while maintaining necessary human supervision and final decision-making authority.

Industry analysts believe that the gradual adoption of AI technology by the nuclear industry marks the industry's ability to embrace technological innovation while maintaining safety standards. Through specialized AI solutions, nuclear power plants can achieve improved operational efficiency within strict regulatory frameworks.

With the completion of this funding round, Nuclearn plans to further expand its product features and market coverage. The company's success also provides a useful reference case for other startups focusing on AI applications in traditional industries, demonstrating how to successfully deploy AI solutions in a highly regulated environment.

From a broader perspective, the combination of AI and the nuclear industry reflects the penetration trend of AI technology in various traditional industries. As AI technology continues to mature and industry acceptance increases, it is expected that more specialized AI solution providers like Nuclearn will emerge in various vertical fields, driving the process of digital transformation in traditional industries.