SoundHound Pays $25 Million for Restaurant AI Firm SYNQ3

SoundHound is acquiring SYNQ3, a company providing restaurants with voice artificial intelligence (AI).

“The deal will make SoundHound the preeminent U.S. provider of voice AI for restaurants, significantly extending its market reach by an order of magnitude to over 10,000 signed locations and accelerating the deployment of leading-edge generative AI capabilities to the industry,” the company said in a Thursday (Dec. 7) press release.

According to the release, SoundHound is expected to pay $25 million to acquire SYNQ3, with the deal set to close in the first quarter of next year.

With the addition of SYNQ3, Soundhound’s customer base will grow to include drive thru, fast casual, casual restaurants and convenience stores, encompassing more than 25 national and multinational chains, the release said.

“In joining forces, SoundHound AI and SYNQ3 will be the go-to standard for cutting-edge voice and conversational AI solutions for the restaurant industry,” said Keyvan Mohajer, CEO and co-founder of SoundHound.

“Restaurant operators are turning to technology en masse, and voice AI is now playing a key role in helping them drive sales, reduce costs, and alleviate the burden of increasing demand on their employees.”

Recent research by PYMNTS intelligence shows how prevalent technology like AI and automation have become to the restaurant sector.

Data from the PYMNTS report “Inflation Puts Technology on the Menu for Restaurants,” a collaboration with American Express, found that 76% of restaurants were using automation in at least three areas of operations.

In addition, data from another PYMTS report, “The Restaurant of the Future Is Open. Will Diners Bite?” showed that quick service restaurants (QSRs) projected that 51% of tasks will be automated by 2025, while full-service restaurants expect to automate 27% of tasks.

PYMNTS’ Karen Webster also spoke with Mohajer about the company’s efforts earlier this year.

“We are trying to combine the best of both the generative AI large language models, which can answer a lot of questions and handle real-time information, with more utility-driven features, and then arbitrate [that combination],” Mohajer said. “The utility domains are good for [direct] assistance, while the LLMs can answer complex questions in real time, so when they are combined there’s a real value proposition.”

He went on to say that conversational AI is a “never ending project” that “will always get better” as the potential for improved recognition and analysis is continually realized.