Nov 13 (Reuters) - California's only remaining nuclear

power plant plans to use artificial intelligence tools to help

it comply with new licensing requirements to keep the

decades-old facility running.

Atomic Canyon, a startup based in San Luis Obispo,

California, said on Wednesday it has signed a deal with Pacific

Gas & Electric (PG&E) to install an AI software

system called Neutron Enterprise at PG&E's Diablo Canyon

facility. The deal, whose value was not disclosed, will help

PG&E sift through decades of documents to create plans to manage

the plant's aging concrete and systems.

Commissioned in 1985 and located about halfway between San

Francisco and Los Angeles on California's coast, Diablo Canyon

was once slated to shut down. California officials reversed

course in 2022 in an effort to stay on track with the state's

carbon-reduction goals.

Maureen Zawalick, vice president of business and technical

services at Diablo Canyon, told Reuters the facility has about

9,000 procedures in place and 9 million documents stored in its

systems, many of them scanned from paper or microfiche. As part

of the PG&E's federal license keep the facility running for up

to 20 more years, the company must create plans to manage it as

it ages, with much of the information drawn from decades-old

documents.

Atomic Canyon's software, which will run on computers

supplied by Nvidia ( NVDA ), will read the documents and make

them searchable in natural language. The startup worked with

researchers at Oak Ridge National Laboratory in Tennessee to

develop an AI model trained to understand the specialized terms

used in nuclear regulatory documents.

Most nuclear plants "have this huge corpus of data, but it

can be really challenging to find documents when you have so

much data that's available," Trey Lauderdale, Atomic Canyon's

founder, told Reuters. "A lot of this data is microfiche. It's

not like they went and labeled what all this data was."

PG&E's Zawalick said the AI system could eventually help

with more complex tasks, like scheduling maintenance on the

plant, which must take into account how all its systems work

together.

Maintenance scheduling is "labor intensive," Zawalick said.

"That's where we're going to gain a lot of efficiencies."