Home / Business / Intelligent recruiting platform Greenhouse picks up another $50M

Intelligent recruiting platform Greenhouse picks up another $50M

Finding the right talent is a make-or-break situation for any company — especially smaller ones, which might not have the robust tools (or pocket books) of larger companies like Google that have a complete system in place. Recruiting platform Greenhouse hopes to make that process a little bit easier, and it has caught the attention of investors.

The company said it has raised a new $50 million financing round from Riverwood Capital, bringing its total funding to $110 million. Greenhouse definitely isn’t the only company that’s starting to pick up a significant amount of funding recently by trying to crack open the process of talent acquisition and make it a little more data-driven. But as the cost and difficulty of collecting enormous amounts of data on different kinds of human activity has dropped with the emergence of new machine learning tools, the problems behind recruiting may also be one that can get a lot of help from employing the same data science rigor that powers a smart Google search result.

“Hiring tools and software in the market had been built for the previous generation, with an applicant tracking mindset to cover the basics of collecting resumes on your website,” Greenhouse CEO Daniel Chait said. “We saw that winning companies in the talent market were ones who were able to attract the right talent, identify difference makers in a sea of LinkedIn profiles, make really smart decisions in who to hire, deliver winning experiences, use data to optimize. They needed tools to accomplish those goals and much broader than the recruiting software.”

The typical consumer’s experience with Greenhouse has probably been a bunch of job listings on a website somewhere, where an employee can submit an application or additional information that the company wants. Under the hood, Greenhouse provides companies with ways to find the right funnels for their applications — whether that’s something like GlassDoor or smaller niches on the Internet with more isolated pockets of talent — and discover the right employees for the roles that are available. Data is collected on all this behavior, which in turn helps Greenhouse give better recommendations for companies as to where to find potential recruits that fit their needs.

All that has to be packaged together with a generally nice user experience, both for the typical consumer and for the companies. That can boil down to actually understanding the right questions to ask, the right requirements to post in a job listing, and also making sure the process is pretty quick for people that are applying for jobs. Greenhouse implements scorecards to help interviewers — which can turn out to be a big group, depending on the position — determine whether or not candidates are the right person for the job in a more rigorous manner. And Greenhouse also hopes to work with companies with its tools to eliminate bias in the recruiting process to produce a more diverse set of hires.

“Companies are continuing to invest in recruiting and talent acquisition software,” Chait said. “As issues of talent and hiring have become more central at the C-suite, companies continue to invest in this area. Companies are starting to see the difference between HR and talent acquisition as its own specialty. If you’re a big company that has an all-in-one HR suite, it’s all well and good to have payroll and benefits in your org chart in one place, but when it comes to hiring, iit’s very dynamic.”

Greenhouse is still pretty dependent on its partners, but the startup has a wide array of companies that it works with to ensure that all the right tools are available to clients to find the right candidates. If a change is coming on LinkedIn — one of the biggest homes of candidate profiles on the planet — Greenhouse is going to work with the company to ensure that nothing breaks, Chait said. Greenhouse provides an API-driven ecosystem to ensure that its tools reach all the right spots on the Internet to help companies find the best talent.

But Greenhouse isn’t the only recruiting-driven company to attract a significant round of funding. It isn’t even the only one to do so in the last month — Hired, another recruiting platform, said it raised $30 million just weeks ago to create a sort of subscription model to help funnel the right candidates to companies. But all this interest, including Greenhouse, is a product of attempts to try to find the right talent in what might be unexpected spots powered by machine learning tools that are now getting to the point where the predictions are actually pretty good.

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Datacoral raises $10M Series A for its data infrastructure service

Datacoral aims to make it easier for enterprises to build data products by abstracting away all of the complex infrastructure to organize and process data. The company today announced that it has raised a $10 million Series A financing round led by Madrona Venture Group, with participation from Social Captial, which also led its $4 million seed round in 2017. Datacoral CEO Raghu Murthy tells me that the company plans to use the new funding to grow its business team in order to be able to reach more potential customers and to expand its engineering team as well. The promise of Datacoral is to offer enterprises an end-to-end data infrastructure that will allow businesses and their data scientists to focus on generating insights over having to manage and integrate their data sources. Since nobody wants to move large amounts of data between clouds — and take the performance hit that comes with that — Datacoral sits right inside a company’s AWS systems. It’s still a fully managed service, though, but the data is encrypted and never leaves a customer’s virtual private cloud. “As companies look to their data to deliver value – data practitioners are finding that configuring and managing their own data infrastructure is a time-consuming job that is expensive and fraught with errors,” said Murthy. “We have built a platform that easily and automatically brings together data from different applications and databases, organizes that data in any query engine and acts on insights that are critical to running their business. A crucial component is that it works securely and privately within the customer’s cloud, instead of us ingesting data from their systems.” Murthy was an early engineer at Facebook and part of the team that was in charge of scaling that company’s data infrastructure and ran a part of the engineering team at Bebop, Diane Greene’s startup that was later acquired by Google. To scale Datacoral, the team is betting on a serverless platform itself. It’s making extensive use of AWS Lambda and other PaaS solutions on Amazon’s cloud computing platform. That doesn’t mean Datacoral plans to only support AWS, though. Murthy tells me that Azure support is next. “We plan to work across all of the top cloud providers by leveraging their unique services and provide a consistent ‘data-centric interface’ to our customers — essentially be ‘cloud best’ instead of ‘cloud agnostic.'” Current Datacoral users include Greenhouse, Front, Ezetap, Swing Education, mPharma and Mason Finance.

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