Seeq, which is bringing big data analysis tools to manufacturers and industrial companies with lots of time-based process data, has filled out a $6 million Series A round led by Second Avenue Partners.
Also participating in the round—which includes a $2 million close Xconomy reported on in May—are Madrona Venture Group, Clear Fir Partners, and angel investors including Gaylord Kellogg of Saltspring Ventures and John Meisenbach, founder of Seattle insurance broker MCM.
Seeq CEO Steve Sliwa says industrial companies in sectors such as oil and gas, chemicals, pharmaceuticals, paper products, and energy are already convinced of the value of their process data—they’ve been collecting it for decades—but they’re not making use of modern big data tools.
An example is an oil refinery, which may have 100,000 sensors, each taking a measurement once a second. The oil company keeps this so-called time series data in software called an enterprise historian for years and uses it for things like compliance, planning, and optimization of billions of dollars worth of assets and hundreds of millions in operating costs, Sliwa says.
But this software can take months to configure, days of specialist work to query, and lacks the flexibility to answer unanticipated questions, he says.
“People in these industries are frustrated. They feel like they have the data. They’ve been collecting it, but it’s still slow and hard to get answers to questions,” Sliwa says.
That’s where Seeq sees its opening. It aims to layer modern big data technologies atop enterprise historians to cut the time it takes to ask questions of this process data down from days to minutes or seconds. It also aims to make this process data more readily available and usable for more people inside a company.
Seeq, which has been relatively quiet since coming together in May, is still keeping its specific technology solution under wraps, Sliwa says.
(Sliwa will, however, talk more about his company and where it’s headed at Xconomy’s upcoming public forum: Big Insight—Making Sense of Big Data in Seattle on Nov. 19.)
There are major players that already sell some $2 billion of software a year to the industries Seeq is targeting, he says.
Competitors include legacy providers of sensor equipment and the makers of enterprise historian software, such as OSIsoft, though Seeq’s software would sit on top of a historian, tying time-series data into other applications and data sources.
Sliwa says the company is in discussions with potential launch customers—all recognizable brands, but none that are ready to be named—with which it would work closely as it develops its software.
The investment in Seeq is part of a substantial flow of venture capital into Northwest big data platforms, tools, and applications companies over the last year. These companies have now raised more than $105 million since September 2012, according to Xconomy research and data from PitchBook Data. Count Tableau Software’s May IPO, and the total climbs to nearly $300 million.
Sliwa says investors were very receptive. “I found good enthusiasm for the idea of applying big data technologies to new verticals,” he says.
Sliwa, formerly CEO of Insitu, the unmanned aerial vehicle maker sold to Boeing for some $400 million in 2008, is tapping both talent from and investors in his prior company for Seeq. The company’s 12 employees include data scientists and engineers from Insitu, as well as OSIsoft, Honeywell, and Microsoft. Seeq investor Second Avenue also invested in Insitu.
While Seeq is nominally based in Seattle, it is actually distributed around the country—part of an effort to stay lean and recruit people who weren’t willing to relocate.
The company’s employees are working from their homes in California, Oregon, Washington, Colorado, and Canada. They use online collaboration tools and get together as a group once every two months.
Sliwa says this has been key to assembling a team of older, more seasoned people including several employees with specific experience in the industries Seeq is targeting.
“There’s no location that we could have picked [to base the company] where we could have had the current team because we couldn’t have convinced them to move,” he says.
Sliwa says you can argue whether the distributed nature of the company adds to or detracts from productivity, but any detriment is trumped by the quality of the team.
