Pattern Recognition, by Ian Sigalow

“Cloud” to “Crowd”



Ian Sigalow

Ian is a co-founder and partner at Greycroft Partners in New York City. He has been a venture capitalist since 2001.


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“Cloud” to “Crowd”

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Crowd ComputingFor the past decade we have all benefited from cloud computing.  You may not realize it, but most Internet companies use some component of the cloud behind the scenes.  Cloud computing cuts down on the cost of launching applications, and as a result we get free services like Instagram, Facebook, Pinterest, and Dropbox that come with infinite storage and more frequent updates than they otherwise would.

At the moment we are entering a new innovation cycle, where the labor market is taking on characteristics of the technology market, with scalable, on-demand labor resources.  This trend is early and doesn’t have its own vocabulary yet, but at Greycroft we call it crowd computing.  There is a big efficiency element to crowd computing, but more importantly it has the potential to create new services.

The NY Times touched on the concept of crowd computing earlier this week, with coverage on how companies are turning to human intervention to improve applications and make sense of mountains of data.  Most companies have teams (ranging from one person to 100,000) who spend all day in front of a terminal manipulating data.  This covers every industry, from healthcare to financial services to consumer packaged goods.  And it is equally common for both large and small businesses.  Even at Greycroft we have two teams of people who spend all day entering data, one focused on portfolio company financial information and the other on pipeline information for our new investments.

If you want to build one of these teams, you either open a satellite office and hire workers, managers, and quality assurance professionals or you go to a business process outsourcing (BPO) provider that has already done some of the legwork.  Either way it is time consuming, inflexible, expensive, and hard.

In 2011 we seed funded a company to fix this problem, called Crowd Computing Systems (CCS).  They offer two different solutions – one is a “public” crowd and another is a “private” crowd.  For people who are familiar with cloud computing this distinction is self-explanatory, but the general idea is that a public crowd is a shared resource that many companies use at the same time, while a private crowd is a dedicated team that only performs work for one company.

CCS’s technology has three components. First, they have a reputation system that scores workers on error rates, availability, throughput, and a number of other factors.  This determines a crowd’s ability to process tasks.  Second, they have tools to break complex processes into simple tasks that can be easily performed in a few seconds.  This is akin to a production line in manufacturing, but for data and complex business processes.  The third and final component is an artificial intelligence system that learns over time from observation.  This allows companies to focus human effort on high skill tasks while pushing redundant work to machines.

While this is still early days for CCS, we recently closed a larger investment to scale the business and they are off to a good start with a handful of Fortune 500 firms including Thomson Reuters, Walmart, Amazon, and Coca-Cola.  I am still waiting on case studies to share but the early data is exciting.  Overall I expect this space will be one of the best areas to watch over the next decade, as well as create major economic change for many companies


Ian Sigalow

Ian is a co-founder and partner at Greycroft Partners in New York City. He has been a venture capitalist since 2001.

  • user

    AUTHOR BenSesser

    Posted on 4:33 pm April 21, 2013.

    I’m really glad I came across this post. Scalable on-demand labor is one of the most interesting trends in my opinion. Everything from what CCS is doing, to platforms for finding, vetting, hiring, and managing distributed labor via mobile (like TaskRabbit or with a vertical application like mystery shopping in the market research space).

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