Databricks is seeking new investment capital to further expand the AI capabilities for its data platform. This is what The Information writes based on insiders. An IPO is ruled out for now, the data specialist itself indicates.
Databricks wants to invest even more in expanding the AI functionality of its data engineering platform due to the growing attention companies are paying to the technology. This platform allows companies to process and transform large amounts of data. The platform also offers many security and observability capabilities for AI solutions and applications.
Recent AI investments
Recently, the data specialist has been significantly expanding the AI capabilities for its platform. Acquisitions include data governance startup Okera, AI storage infrastructure provider Rubicon and, more recently, MosaicML, for undisclosed sums.
In addition, Databricks launched its own generative AI model, Dolly, this year to be an alternative to OpenAI’s GPT models. Other AI solutions and tools introduced this year include LakehouseIQ, a generative AI application development platform, and a Unity catalog as a central place for searching analytics data.
Quest for investment capital
According to The Information, this is still not enough and Databricks is therefore seeking new investment capital. How much the data specialist wants to raise in new capital is unknown.
The search for this capital comes at a time when the data specialist is roughly breaking even. Despite a loss of 827 million euros ($900 million) in the past two years, Databricks says it managed to pass the 919 million euro (the famous $1 billion) turnover mark at the beginning of this year.
No IPO in sight
Databricks’ eagerness to raise investment capital is further fueled by the fact that the company is not seeking an IPO for the time being. Recently, CEO Ali Ghodsi told Bloomberg that an IPO is not on the cards. According to him, the stock market climate is still unfavourable and the status of being a private company actually gives many advantages to Databricks.
As a private company, the data specialist can invest much more easily in AI functionality because it does not have to constantly answer to shareholders. In the latter case, it would have been harder to justify the likely many millions of dollars for its recent acquisitions.
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