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Seattle-Based Recruitment Automation Startup Humanly Raises $12M in Series A Round

Seattle-Based Recruitment Automation Startup Humanly Raises M in Series A Round

Seattle-Based Recruitment Automation Startup Humanly Raises $12M in Series A Round

Humanly, a Seattle-based HRTech startup that helps companies automate their recruiting functions, has raised $12 million in its Series A  round led by Drive Capital. With this investment round, the company plans to grow its engineering and go-to-market teams.

The startup’s goal is to automate mundane tasks for human resources personnel so they can focus on building deeper connections with candidates. Its technology also helps with interviews by providing automated notes, follow-up emails and insights. It claims to have processed more than 1 million job candidates, including for clients such as Microsoft, the restaurant chain Fazoli’s and Seattle-based accounting and consulting firm Moss Adams.

Co-founded by Prem Kumar, Andrew Gardner and Bryan Leptich in 2019, Humanly provides artificial intelligence-powered chat that handles tasks like screening, scheduling and re-engaging with candidates. The platform’s chat technology can also help with reference checks.

Speaking about the company, Co-founder & CEO of Humanly, Prem Kumar, said:

Any conversation you’re having with job candidates, via SMS chatbot or human, we want to be there and make those more efficient and more equitable. The startup aims to address a pain point in the hiring process where limited data is exchanged between hiring managers’ bots, screening tools, and interview transcripts. Multiple devices often make candidates feel like they are “being interviewed by three companies.

Humanly’s library of conversational interactions is stripped of bias triggers such as gendered words, culture-specific terminology, lines of questions that bias towards certain cognitive processes, and even role-specific biases. It optionally allows customers to hide fields like a candidate’s name, so hiring teams can focus on factors predictive of success per role, industry, and market.

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