ThoughtSpot Raises $50M for Business Data Search Engine

“The consumption of data by humans has increased maybe millions of times compared to what we used to use,” Ajeet Singh says. “This is possible because of search.”

By that, serial entrepreneur Singh means search engines like Google and Microsoft’s Bing, which instantly scour websites to find us a restaurant, an audiobook, or the name of an actor that eludes us. But Singh (pictured) is also one of the innovators who have been extending the territories of data that can be interrogated by new machines seeking quick answers, patterns, or simply unexpected caches of compelling information.

After years working at Oracle and other companies that contributed to a vast expansion of data storage capacity for businesses, Singh was struck by the lack of technological changes that could allow companies to quickly tap into their new troves of useful information as they made decisions.

In 2012 he co-founded ThoughtSpot, which created a search engine designed to allow businesses—and even their non-technical decision makers—to mine in-house databases for insights and numbers that could guide them in their next steps.

Palo Alto, CA-based ThoughtSpot announced today it raised $50 million in a Series C funding round that brings its total fundraising to $90 million. The round was led by General Catalyst Partners, joined by Geodesic Capital and previous investors Lightspeed Venture Partners and Khosla Ventures. The company doesn’t disclose its revenues or its number of customers. But Singh says the customers are mainly mid-sized to large enterprises in North America and Europe. They include Bed Bath & Beyond, Primary Capital Mortgage, RichRelevance, Automated Financial Systems, and Collegis Education, the company says.

ThoughtSpot plans to use its new capital to continue a global expansion that began with the opening of a London office in January. One of its investors, Geodesic Capital, was founded last year to support the expansion of U.S. companies into Japan and Asia. Singh says ThoughtSpot will start branching out into Japan within six to 12 months. The company’s staff of 120 will be growing, he says.

ThoughtSpot has plenty of company in its field—a raft of other startups offer data analytics services to businesses. They include Newton, MA-based Attivio; Seattle-based Tableau Software; and Redwood City, CA-based Interana.

The power of search has inspired many other entrepreneurs to apply it in new contexts. Innovators have adapted search engines to ferret out specific gene sequences within huge genomic databases (San Francisco-based Reference Genomics); to index previously unstructured data from comment sections, advertisements, and message forums (Palo Alto-based Diffbot); to search images using a “key word” that is itself an image (Palo Alto-based Superfish); and to help users retrieve their files when they’ve forgotten where they socked them away among their many Web-based storage sites (San Francisco startup Xendo, acquired by AppDirect.)

Singh says the challenge for ThoughtSpot was to create a high-powered computational engine that could apply the search function to numbers.

“We had to build something from scratch,” Singh says. Team members drew on their experiences working on search infrastructures at Google, Microsoft, and other companies, he says.

The startup also wanted to make its search engine so easy to use that it wouldn’t be a tool only for a company’s business intelligence experts and data scientists. Those analysts already can’t keep up with the barrage of questions from non-technical employees who want to make informed decisions, Singh says. These might include fashion buyers who need past sales figures for particular shirts in particular regions, for example; or marketing managers who want to know how well an ad campaign performed; or insurance sales reps asking how a new addition to a client’s family should affect the rates on a renewed policy.

Singh says ThoughtSpot distinguishes itself from its competitors by an ease of use he calls “analytics for humans.” A staffer can begin using the search engine after a half-hour orientation, while other products require as much as three days of training, he says.

The search engine’s accessibility to novices at data analytics is no threat to the job security of business intelligence experts who have university degrees in data science, Singh says. Those specialists can stop doing things below their pay grade and focus on projects like statistical analyses that can point to tactics such as “the best way to catch people doing fraud online,” Singh says.

While ThoughSpot’s search engine guides non-technical users so they can frame their questions well, it can’t tell when a user is asking for data that is irrelevant to the decision they’re trying to make, or would even be misleading, Singh says.

“The machines don’t understand business—they’re not good at judgment calls,” Singh says. But in the future, maybe they’ll acquire such skills, he speculates. “Potentially, that’s where the world is headed in the next 10 to 15 years.”

Bernadette Tansey is Xconomy's San Francisco Editor. You can reach her at btansey@xconomy.com. Follow @Tansey_Xconomy

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