Ex-Uber and Palantir tech leads are using AI to remove bias from hiring with their new startup. Check out the 18-slide pitch deck Metaview used to raise $6 million. – Markets Insider

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Metaview
A startup that has developed an AI platform that helps to remove bias from the hiring process has raised $6 million in a seed round.
London-based Metaview enables hiring managers to take a data-driven approach to filling roles instead of relying on gut feeling, resumes, and memory.
Managers can record and transcribe all interviews and tap into analysis revealing where the interviewers need to improve. Areas of improvement could be the number of questions that were asked, how questions were phrased, how long candidates were given to speak, how well parties were able to build a rapport, and the overall structure of the interview. 
Individual interviewers also receive weekly feedback reports that help to identify unconscious bias and suggest improvements. Feedback is benchmarked against anonymous, aggregated data from across the company.
Metaview cofounder Siadhal Magos, who was once a product lead at Uber, said it was difficult for any organization "no matter how forward-thinking they are, how technologically advanced they are" to systematically improve interviews due to a lack of data.
Magos was involved in the hiring process at Uber and said the company made hiring a "centrally-important process" that operators, builders, and engineers were all involved in.
"But the tooling that we had meant that, actually, we still felt those processes were pretty unreliable," he said.
"You often made hires who didn't work out or folks who weren't the right fit for the team, or we were really pumped about a candidate and maybe they didn't accept the offer."
In 2016 he joined forces with then-Palantir engineering lead Shahriar Tajbakhsh and the pair set out to make the interview process more rigorous, consistent, and fair.
"There were all these suboptimal outcomes of the hiring process that were really different to what we experienced when we were building a product," Magos added.
"We thought we had really good control and really good oversight of the product process. That's really the big thing that drove Metaview; this idea of 'how do we start to power these people decisions with the same truth that we have when we're building our products?'"
According to the startup's own data, women have 12% less speaking time than men, while a quarter of hiring managers ask less than five questions per candidate.
It can only identify potential gender and ethnicity bias if the customer provides candidate data, and does not predict an interviewee's demographic. 
Metaview's sweet spot is high-growth companies whose leaders cannot be present in interviews and have a headcount of around 200 to 5,000 people – "where you're beyond the scenario where everyone knows each other."
Its current customer base includes high-profile trading platform Robinhood, drone company Anduril, startup jobs site AngelList, and sports analysis company Hudl. Its biggest competitors are in-house interview solutions, Magos said, though they "tend to be pretty analog processes."
The fresh cash brings Metaview's total raised to $7.6 million, following a pre-seed round. 
It will be used to increase headcount from 10 to 30 through 2022 with roles in product and sales, and cement its presence in Europe and the US. 
The round was led by early-stage investors Vertex Ventures US, alongside automation specialists Fly Ventures, Seedcamp, Village Global, and PrimeSet. Moving Capital and Palumni, Uber and Palantir respective alumni funds, also participated in the round.
Check out the pitch deck Metaview used to entice investors below.
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