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On Monday, the mental health startups announced that SonderMind, which connects patients and clinicians, acquired Qntfy, a scrappy data and machine-learning company, for an undisclosed amount. The acquisition took around four months to finalize after founders Mark Frank of SonderMind and Glen Coppersmith met in May this year based on a recommendation by a mutual contact.
“We weren’t actively looking to be acquired at that point in time,” Coppersmith told Crunchbase News. “It just was so obvious that this is the right match. … and this thing moved relatively quickly once we realized that we are clearly attacking the same problem and the same challenge, but coming to it from very different perspectives and very different techniques.”
The two founders told Crunchbase News that the acquisition is another proof-point for where mental health tech and treatment is heading: From primarily subjective reporting by patients seeking face-time with an increasingly outnumbered slate of licensed therapists, to care models that are more data-driven and helped along by artificial intelligence or other tech.
Indeed, technology is becoming a growing part of the mental health industry. An ever-increasing selection of wearables can now track everything from sleep to steps to mood, while chatbots triage people looking for connection online. Scientists and startups have also started to use brain imaging technology to map out mental health treatments and even design new drugs.
Denver-based SonderMind has been working since 2017 to make easier the sometimes grueling task of finding a therapist who is a good match for a patient and takes their insurance. The company has raised more than $180 million in funding over 5 rounds, including a Series C round on July 28, Crunchbase data show.
Arlington, Virginia-based Qntfy, which was founded in 2014, built its revenue primarily off of business contracts “the old-fashioned way,” rather than funding rounds, said Coppersmith, who will join SonderMind as the new chief data officer.
The Qntfy platform aims to gather additional mental health and biometric data—with permission from patients—from things like health applications and trackers, wearables or other devices. From there, it can analyze the information and help identify treatment recommendations through machine learning.
That’s the kind of technology that was attractive to Frank as SonderMind looked to expand its data science team, he said.
“We were focused on ‘How can we leverage this important part of our health care community—these providers who are delivering mental health care, who are in such [demand], and are overextended—in a way that isn’t being done?’” he said. “It’s really about how we can make the care itself more effective, and if it’s more effective than maybe it’s also a little bit more efficient.”
Illustration: Dom Guzman
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