That agent who sounds like he’s from Paris, Texas? Try Paris, France

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Our daily life more connected in a globalized grid than ever before. Products are purchased and delivered from afar; getting to a place 3,000 miles away may be easier than crossing a big city in traffic; and information is distributed to anyone and everyone at the touch of a finger.

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startup called Sanas has developed AI voice technology that aims to make one of the critical components of this network smoother – how people who speak the same language but with different accents can better understand each other by filtering accented voices and turning those accents into real-time other. . Today, the startup is announcing $32 million in funding on the heels of strong momentum for its tools as it emerges from stealth and launches more widely.

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Insight Partners is leading the investment with new sponsors GV (formerly Google Ventures), strategic sponsor Assurant Ventures and angel investor Gokul Rajaram. Previous sponsors Human Capital, General Catalyst, Quiet Capital and DN Capital are also participating in this Series A round. Along with the investment, Sanas is also announcing a strategic partnership with Alorica, one of the largest BPOs in the world that is bringing the technology to 100,000 employees and 250 corporate clients around the world.

The company does not disclose the valuation, but we understand it to be $150 million after cash. This Series A is one of the largest for a voice AI startup, and we understand it began after Sanas turned down an acquisition offer from Google. (If you can’t buy them, invest in them!)

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As you might have guessed from the list of investors, Sanas’ technology is already being rolled out to call centers. In particular, he has found great support from customer service providers, who have become a breeding ground for abuse of agents who can speak the same language as the customer but with a heavy accent.

In addition to insurance giant Assurant and BPO leviathan Alorica, other clients include major collection firm ERC and travel company BPO IGT. In a sad commentary on the state of our world, Sanas CEO and co-founder Maxim Serebryakov said the result of using the technology in these places has been impressive in terms of reducing agent harassment.

Sanas’ plan is to use the funding both to continue expanding his business in this vertical and to start preparing for other enterprise use cases, such as a video call plug-in or interactive voice services. to help machines (and machine learning based systems) understand a wider range of accents.

Serebryakov originally co-founded the company with Shawn Zhang and Andrés Pérez Soderi, two fellow students at the Stanford AI Lab, after their fourth friend had to drop out of school and return to his home country, Nicaragua, to take a job to help with a family emergency.

A friend took a job at a call center in his home country servicing clients in the US, and although he was perfectly fluent – and no less than a student taking a break from Stanford – he faced endless phone harassment from people who didn’t like his accent. .

The other three understood this judgment, reaction, and abuse all too well, since they were first-generation immigrants themselves (and I will add that I know this very well first-hand, both in my current life and as a child). first-generation immigrant to the United States). And so they decided to test their AI knowledge to see if they could fix it. (Earlier this year, Sanas also hired a fourth co-founder, Sharath Keshava, who is now also COO, who left another company he co-founded,, after learning about the company and wanting to be involved in its creation. )

Today, there are many tools for “auto-tuning” and changing a person’s voice in real time or with a delay – at the moment they are about as common as photo filters. But, as Serebryakov notes, it is especially difficult to keep a natural, real voice and change the way he says what he says.

Interestingly, the problem is so abstract – Sanas approached it by incorporating thousands of hours of speech with different accents into the system and arranging it according to other sounds, with all the combination of technologies and methods that are now also patented. process – that the end result is that Sanas’ accent “translation” mechanism can be used with any language in general, not just English, as you might assume. (Serebryakov tells me that it is already being used to “smooth out” accents, for example, in Japan, China, and South Korea.

“Such technologies are applicable globally, from one accent to another,” he said. “It will take time, but our goal is to allow people to communicate with any accent.”

There is a certain unease around the very concept of what Sanas does and what he does here. This raises many questions about potential abuse, and furthermore, some may find it obnoxious and outdated that technology is being developed specifically to hide a person’s true identity: shouldn’t people who judge by an accent, those who should learn to be more open-minded and accepting, rather than people who are forever conforming to prejudices, hiding everything that distinguishes others from outsiders or others?

However, there are also arguments against this. At this time, Sanas specifically does not create any applications for consumers and does not make its technologies available to them, precisely because it can be misused. Even its customers don’t use the cloud version of the technology: for added security, it’s hosted locally, so customers control their own data that passes and is generated through Sanas.

As for hiding one’s true identity, this is certainly a more serious problem that we all need to deal with on a daily basis. In the meantime, it gives those at the cutting edge of these blows a way to get along better, and in some very practical ways makes it easier for people (even those with good intentions) to simply understand each other without accents getting in the way.

I had a service demo during my interview when Sanas called one of his clients’ agents in India and had him chat with me first in his own accent and then “turning on” his Midwestern neutral tone. It was a little creepy to know what was happening in the background, but at first glance I was very surprised at how natural it all seemed – well, natural enough at least. His voice was clear, but maybe too clear, almost mechanical and devoid of emotion.

Apparently, this is also done intentionally at the moment and can be developed if customers and other users want it.

“The reason we’re concentrating on call centers is because it’s a low-hanging fruit,” Serebryakov said, noting that the difficulties of creating a truly groundbreaking technology were quite difficult, but it also fits the use case. “For us, when building this, it was important to take the path of least resistance. No singing, no laughter, no hyper-emotional speech. We’re trying to give control over how these users interact at work.” There’s no crying in baseball, and there’s no fun or games in the call center either.

“Insight Partners is thrilled to deepen its relationship with Sanas on such cutting-edge and transformative technologies,” said Ganesh Bell, Managing Director of Insight, in a statement. “As the company moves out of its stealth phase, I look forward to working with this extremely talented and passionate team to create a product that, among other things, will help eliminate the annoying prejudice and discrimination faced by those who speak English. English as a second. language in which many Sanas employees are involved.”

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