This Series L round would value the company at $134 billion, up 34% from its last session of funding during the summer, the Wall Street Journal (WSJ) reported Tuesday (Dec. 16).
Ali Ghodsi, Databricks’ co-founder and CEO, told the WSJ the company plans to use the new funding to invest in its core data-analytics products and AI software, while also letting its workers engage in secondary share sales.
The company, among the most valuable private firms in Silicon Valley, also plans to hire around 600 fresh college graduates in 2026, the CEO added, in addition to adding thousands of new jobs worldwide in Asia, Latin America and Europe. It also plans to hire AI researchers, who are typically paid top salaries, the WSJ added.
The report noted that Databricks has benefited from the AI boom, which relies partially on private corporate data to customize AI models. Databricks told the WSJ that its data-warehousing product, which can serve as an underlying data platform for AI services, surpassed a $1 billion revenue run rate at the end of October.
This year has seen Databricks ink deals with OpenAI and Anthropic to help sell AI services to business customers. Each of these partnerships are designed to push clients to develop AI agents, or independent bots that can carry out tasks on behalf of humans.
The company’s new funding round comes three months after Databricks’ Series K round, which valued it more than $100 billion, up from $62 billion at the start of the year.
In other AI news, PYMNTS wrote earlier this week about The General Intelligence Company of New York, a start up developing agent-based systems designed to take over large portions of company operations.
“The company’s name deliberately evokes Gilded Age ambition, and founder Andrew Pignanelli told PYMNTS that the reference was intentional,” that report said. “He said he views AI as foundational infrastructure for the next era of company-building, much as railroads and industrial capital reshaped the United States economy more than a century ago.”
The company started by working backward from “the one-person billion-dollar business,” as Pignanelli termed it.
“We started at the end, the actual one-person billion-dollar company, and worked our way back and we were like, ‘What can we do today?’” he said.