Data analytics firm Databricks said on Monday it was on track to hit $4 billion in annualized revenue on the back of booming demand for its artificial intelligence products, as it closed a $1 billion funding round.
The Series K funding valued the company at $100 billion, making it one of the most valuable private companies in the world. The round was co-led by existing investors Andreessen Horowitz, Insight Partners, MGX, Thrive Capital and WCM Investment Management.
The company plans to use the proceeds to accelerate its AI strategy, including expanding products, launching a new operational database category, and future AI acquisitions and research.
In the second quarter, the company served around 15,000 customers, including energy major Shell and electric-vehicle maker Rivian, surpassing a $4 billion revenue run rate, with AI products reaching $1 billion.
Databricks is targeting a net revenue retention above 140 per cent, more than 650 customers with more than $1 million in annual spending and positive free cash flow over the past 12 months, the company said.
CEO Ali Ghodsi said the company intends to remain cash-flow positive, which could keep the door open for an initial public listing, without committing to any specific timeline.
The raise could help the company invest more in AI products such as Agent Bricks, a platform that helps people build AI autonomous systems, as well as its data warehouse product Lakebase, which has already generated tens of millions in annualized revenue since its launch in June. It has been actively making acquisitions, including the recent buy of machine learning startup Tecton.
The San Francisco-based company has long been seen as a leading candidate to go public. The firm has received numerous investor inquiries since the successful $1.22 billion initial public offering of design software firm Figma, another venture capital-backed startup, in July, according to Ghodsi.
Databricks, founded in 2013, offers a platform designed to help users ingest, analyze and build AI applications.
