Atomic Canyon Wants to Revolutionize Nuclear Knowledge Like ChatGPT Did for Conversation

28.05.2025

Tech companies are placing big bets on nuclear power to meet the massive energy demands of AI development. But while AI is moving fast, nuclear energy isn’t known for its speed. Trey Lauderdale, founder of Atomic Canyon, believes AI itself could help accelerate nuclear energy’s pace—especially by tackling one of its biggest obstacles: information overload.

Lauderdale’s inspiration came from his own backyard in San Luis Obispo, California, where many locals work at the nearby Diablo Canyon Power Plant. Through conversations with them, he discovered that nuclear facilities manage billions of pages of documents—Diablo Canyon alone houses around 2 billion. With a background in healthcare tech, Lauderdale saw an opportunity to apply AI to make that information more accessible and useful.

He launched Atomic Canyon about a year and a half ago, initially self-funded, aiming to assist engineers, technicians, and compliance teams in finding critical documents quickly. In late 2024, the startup secured a deal with Diablo Canyon, which sparked interest from other plants. This traction prompted Lauderdale to raise capital, leading to a $7 million seed round led by Energy Impact Partners and other investors.

Developing effective AI tools for the nuclear sector wasn’t easy. Early tests revealed that general-purpose AI models struggled with the complex and acronym-heavy language of nuclear documentation. Lauderdale turned to Oak Ridge National Laboratory, which granted Atomic Canyon 20,000 GPU hours on its supercomputer to help train custom models. The startup now uses sentence embeddings and retrieval-augmented generation (RAG) to make nuclear documentation searchable and reduce hallucinations in responses.

Currently, Atomic Canyon focuses on safe, low-risk applications like document title generation and search indexing. Lauderdale stresses that the goal is not full automation but intelligent assistance, always with a human in the loop. While document search is just the beginning, it’s a critical foundation—one that offers a long runway as the company works toward more advanced AI-assisted nuclear workflows.