Siadhal Magos and Shahriar Tajbakhsh were working at Uber and Palantir respectively when they both realized that recruiting (especially the interview process) was becoming unmanageable for many corporate HR departments.

“We’re well aware that the interview is the most important part of the hiring process, but it’s also the least transparent and unreliable,” Magos told TechCrunch. “On top of that, there’s a lot of tedious work associated with taking notes and writing feedback that many interviewers and hiring managers go to great lengths to avoid. “

Magos and Tajbakhsh believe the hiring process is ripe for disruption, but they want to avoid taking too much of the human element out. So they launched Metaview, an AI-powered note-taking app for recruiters and hiring managers to record, analyze, and summarize job interviews.

“Metaview is an AI-powered note-taking tool built specifically for the recruiting process,” says Magos. “It helps recruiters and hiring managers focus more on getting to know the candidate rather than extracting data from the conversation. As a result, recruiters and hiring managers save a lot of time writing notes and can be more actively engaged during interviews, Because they don’t have to multitask.”

Metaview integrates with apps, phone systems, video conferencing platforms, and tools like Calendly and GoodTime to automatically capture interviews. Magos said the platform “takes into account the nuances of recruiting conversations” and “enriches itself with data from other sources, such as applicant tracking systems” to highlight the most relevant moments.

“Zoom, Microsoft Teams and Google Meet all have built-in transcription capabilities, which could be alternatives to Metaview,” Magos said. “But the information Metaview’s AI extracts from interviews is far more relevant to recruiting use cases than generic alternatives, and we also help users take next steps in the recruiting workflow in and around these conversations.”


Image Source: Yuanshi

Of course, there are plenty of problems with traditional job interviews, and note-taking and conversation analysis apps like Metaview can help, at least in theory. As an article in Psychology Today points out, the human brain is full of biases that hinder our judgment and decision-making, such as the tendency to rely too heavily on the first piece of information presented and in a way that confirms our pre-existing beliefs Interpret the information.

The question is, does Metaview work? More importantly, will it work equally well for all users?

Even the best AI voice dictation systems are subject to their own biases. A study from Stanford University found that black people make nearly twice as many errors as white people when using speech-to-text services from Amazon, Apple, Google, IBM and Microsoft. Another recent study, published in the journal Computer Speech and Language, found statistically significant differences in the way two leading speech recognition models treat speakers of different genders, ages and accents.

There are also hallucinations to consider. AI makes mistakes when summarizing, including in meeting summaries. In a recent report, The Wall Street Journal cited an example where an early adopter used Microsoft’s AI Copilot tool to summarize a meeting, with Copilot fictionalizing attendees and suggesting the call covered topics that had never been discussed.

When asked what steps, if any, Metaview takes to mitigate bias and other algorithmic issues, Magos claimed that Metaview’s training data is diverse enough to produce models that “superhuman performance” in recruiting workflows, and Performs well on popular bias benchmarks.

I’m skeptical and a bit cautious about Metaview’s approach to handling voice data. Metaview stores conversation data for two years by default, unless the user requests it be deleted, Magos said. This may seem like an unusually long time, as may the candidate.

But none of this appears to have affected Metaview’s ability to secure funding or customers.

Metaview raised $7 million this month from investors including Plural, Coelius Capital and Vertex Ventures, bringing the London-based startup’s total funding to $14 million. Magos said Metaview’s customer base has reached 500 companies, including Brex, Quora, Pleo and Improbable, and has grown 2,000% year-over-year.

“This funding will be used primarily to grow the product and engineering teams and provide additional momentum to our sales and marketing efforts,” Magos said. “We will triple our product and engineering teams, further fine-tune our conversational synthesis engine so that our AI can automatically extract the right information our customers need, and develop systems to proactively detect issues such as inconsistencies during interviews and Candidates who don’t seem to fit the bill. Lose interest.”

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