Bottlenose Scores $13.4M To Help Enterprises Spot Emerging Trends And Threats In Real-Time

Bottlenose, a big data analytics firm which likens itself to “a real-time Palantir,” referencing its focus on tracking, filtering and analyzing stream data, has raised $13.4 million in Series B funding, an SEC filing shows and the company now confirms. The round was led by KPMG Capital, a new fund created by KPMG International to invest in data and analytics globally. Bottlenose is the first public and significant investment the fund has made, notes company co-founder and CEO Nova Spivack.

News of KPMG’s involvement in Bottlenose was announced back in December, when it was revealed that KPMG Capital would now have a “substantial equity share” in the company. However, that news was only a part of the overall funding event, which also see new investor Origin Ventures joining alongside returning investors, including Lerer Ventures, Transmedia Capital, ff Venture Capital, and others.

To date, Bottlenose has raised roughly $17 million.

Spivack says that while the company has now closed on $13.4 million, the round allows the company to raise more. “But we don’t necessarily need to or have to,” he says. “The money is sufficient for what we need to do…we do have some interest, and there are some discussions happening,” Spivack says. In addition, Bottlenose plans to raise significant venture debt on top of the $13.4 million, which itself was a combination of mostly equity and debt. (Bottlenose may offer an update when the round officially closes).

The funding will go towards helping the company continue to grow the business, expanding both its product line and team, which today numbers around 40 full-time and will head towards 80, thanks to the new capital.

Bottlenose, by way of background, offers large enterprise customers a high-performance, cloud-based solution that’s capable of analyzing massive amounts of real-time data, in order to proactively identify things like emerging risks, threats, crises, opportunities, breaking news, and more.

To put its capabilities into perspective, Twitter currently sees around a billion messages a day on its service, says Spivack, while Bottlenose is now analyzing 72 billion data records and messages daily.

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The company began its life focusing on social stream data – that is, data streaming out from social networks and services which marketers wanted to analyze quickly. But it soon found product-market fit within large global players, expanding first into research and then enterprise data. To date, Bottlenose has worked with 18 global organizations, including names like Pepsi, Warner Bros., DigitasLBI, Razorfish, FleishmanHillard, and others.

It has since expanded far beyond social data, too. It now analyzes 98% of live TV and radio data in real-time, says Spivack – that’s 40 hours of video and audio per minute being measured using speech-to-text conversions. It’s also now adding in enterprise data sources, including things like sales data, log data, transaction data, and even firewall data.

In fact, detecting intrusions is a growing opportunity for Bottlenose, given how prevalent data breaches are these days. Explains the CEO, what makes the product’s capabilities so interesting here is its ability to correlate data from across sources. “If hackers are talking about a company, and we see also corresponding, correlated activity on that company’s firewall, that’s actually a good indicator that there’s actually something happening,” says Spivack. Some of Bottlenose’s now eight patents cover these sorts of capabilities, he adds.

What’s different about Bottlenose’s system is that its customers don’t need to know what they’re looking for in order for the data to be useful. Instead, Bottlenose just analyzes everything that comes in, and is then able to point companies to emerging threats and issues, whether that’s a new competitor, or even just a new opportunity.

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“We analyze everything we see…by doing that, we find these unknown things you didn’t know to ask for,” Spivack explains. “The system is designed to handle any kind of data – structured or unstructured…if it’s stream data, our system is designed to make sense of that.”

Unlike companies like Palantir, which tends to work with static data sets, Bottlenose customers tend to use its system in a number of areas where data needs to be analyzed in real-time, because time is a key advantage. That includes things like financial services, trading, real-time ad buying, or even fending off attacks.

(Of note: while Spivack wouldn’t confirm Palantir’s interest specifically, he would say that there have been offers in the past that he turned down in terms of acquisitions.)

Today, Bottlenose reaches its customers through a cloud-based solution known as Nerve Center, but Spivack says that later this year, they’ll be making some announcements related to becoming more of a full-stack company.

“There will be a lot of interesting news about the platform later this year,” he hints.