Dataminr, the $4B big data startup, is laying off 20% of staff today, or 150 people, as it preps to double down on AI

It’s a tough day for Dataminr, the New York-based big data unicorn last valued at $4.1 billion. TechCrunch has learned that the company — which AI and big data algorithms to provide predictive insights about news and other global events, is laying off about 20% of staff today, or around 150 people. It cites the impact of the economic environment, operational efficiencies, and “the recent rapid advancements of our AI platform,” according to a memo from founder and CEO Ted Bailey, shared with us by a source.

In the company-wide memo that we have seen, staff were told to work from home today while they waited for details on whether they would be part of the impacted group of employees. The company had been signalling to staff since October that a restructuring was coming, although it’s not clear what business areas are being affected, nor what the state of the company’s business has been like recently.

Bailey noted in the memo that the restructuring measures will “put Dataminr on a very strong financial footing moving forward.” The company will be looking to further progress its AI platform and products — specifically with the launch of a new AI platform in Q1 that will combine predictive AI with generative AI — but even with the investment that those will require, as a result of the moves it’s making today, “Dataminr will have multiple years of cash runway and a near-term path to profitability,” he continued. (That potentially also implies that it’s setting itself up for a scenario in which it won’t be raising more outside funding.)

We have reached out to Bailey, the company’s media relations team, and to various other individuals to confirm the details provided to us by a source (who, unfortunately, appears to be among those impacted: really sorry again, friend). One of those individuals, who asked not to be named, also confirmed the details. In the meantime, there are now posts on LinkedIn from others hearing the news through the grapevine and looking to hire.

And just as we were about to hit publish on this, a spokesperson from the company confirmed the memo to us.

Dataminr, founded in 2009, first came to prominence at a time when we were seeing the emergence of companies using clever big data techniques to parse unstructured data from social media posts and combining it with structured and unstructured data from other sources to understand public sentiment and other insights.

Dataminr took that concept and applied it squarely to insights about global events and other news: users equipped with mobile phones used platforms like Twitter as an outlet to post about something they were seeing: Dataminr tapped into this, combined it with other data sources, and was able to pick up a development right as it was happening, often ahead of the rest of the world jumping on the news.

Unsurprisingly, some of the data it gathered and how it got used has courted controversy over the years. But that didn’t appear to stop the company from gaining traction. Dataminr found success with key partnerships with companies like Twitter, and customers in government, enterprise, financial services and media.

And in the heady funding days of the 2010 decade, it raised money — a lot of it. It was last valued at $4.1 billion when it raised $475 million in 2021. Overall, it has raised more than $1 billion, with its 100+ investors including the likes of Fidelity and Morgan Stanley, as well as Venrock, IVP and many more. (Twitter, now called X, was once also an investor although it divested its stake some time ago.) PitchBook data indicates that it raised an undisclosed sum in further funding in two different tranches in the last year.

Dataminr has always had a large number of “subject experts” that it had on staff alongside engineers and sales and customer success specialists. In more recent years, and most likely this year, the company has really doubled down on the AI aspect of its tech stack, one reason why it might see a route forward downsizing its workforce without impacting business.

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