In today’s outsourcing tech marketplace, you can find freelancers for almost anything, from mobile marketers on Elance to algorithms on Algorithmia.
Boston-based Experfy is building on the fact that companies, especially larger ones with more than $50 million in revenue, have heaps of data that they sometimes don’t know how to use. Experfy lists engineers and data scientists who are available to be contracted out for single or multiple projects, and helps its mid-to large-size business customers create a project for those experts to bid on with proposals, according to co-founder and co-CEO Harpreet Singh.
After an account manager helps a business customer develop a project—a revenue management system, say, or an algorithm to automate a business procedure—Experfy’s own algorithms will select experts to suggest for the plan, Singh says. Most projects get 20 bids on average from the 1,350 data experts who have already been verified by Experfy, he says.
“People don’t really know how to use [big data] for their business. They know it gives them a competitive advantage, but not how exactly to use it,” Singh says. “We have a lot of data scientists who want to join, but we are selective of who gets in.”
Experfy also uses an algorithm to select, investigate, and approve whether a data scientist gets listed on its platform, according to co-founder and co-CEO Sarabjot Kaur. If there are subjective elements to deciding whether to approve an expert, the company will interview the candidate, Kaur says.
It has 6,000 others who have created an account and submitted an application, she says. The company, founded in January 2014 and housed at the Harvard Innovation Lab, hopes to one day have 20,000 in its system.
Experfy is at a moment of expansion after securing $1.5 million in seed funding last week led by Peter Diamandis, CEO and chairman of nonprofit XPrize, as first reported by The Wall Street Journal today. Diamandis contracted Experfy to help him appropriately connect attendees with one another at a conference of executives of mid- and large-sized companies, the Journal reported (and Kaur says).
After Experfy helped Diamandis, he invited the startup to speak at the conference, Kaur says. Some of the executives there also invested in the company’s seed round, she says.
Experfy had previously been focused only on Fortune 500 businesses, and the interest from CEOs of mid-size businesses at conference showed they could be customers too, Kaur says. “It was really an eye opener for us in terms of our target market,” she says.
Now Experfy is using the seed funding to expand marketing and sales efforts, planning as many as seven hires this year on top of 10 current employees, Singh says. The funding should last through next year, Kaur says.
Projects the company has worked on cost $10,000 to $20,000 on average, and last around a month, Singh says. The company takes 20 percent of the fee, giving the other 80 percent to the data scientist who wins the contract, he says.
Other companies are targeting related, if not the same, markets. Seattle-based Algorithmia offers a service that charges a per-use fee to lease out one of hundreds of algorithms that the company has built, with the company or individual using it unleashing the algorithm on data they want processed, as Benjamin Romano wrote in March. Skillbridge connects businesses in need of advice or consulting with a group of experts and MBAs to make a short-term contract.
While there is certainly some overlap, and Experfy does want to offer top-level experts as consultants-for-hire, those other businesses don’t have as much of a focus on Experfy’s bread and butter, which is data science, Kaur says. And companies such as Cloudera, Hortonworks, MongoDB, Tamr offer tools, while Experfy offers skilled humans who can use them, Singh contends.
“We provide the expertise to leverage those tools,” he says.
Singh considers large consulting firms such as Deloitte or McKinsey more direct competitors, and isn’t intimidated by their size or scale. “We’re eating their lunch,” he says. “Our standard pitch is that we are three to five times cheaper than the big four, and we are three to five times faster, without sacrificing the quality.”
