Published On: Thu, May 30th, 2019

Mental Health startup Talkspace raises $50 million

Talkspace connects users with therapists via chat and video. The company has raised $106.7 million since establishment in 2012

New York-based Talkspace, which provides mental therapy via a subscription-based online platform, has just raised $50 million to help reach more users.

Founded by Israeli husband and wife, Oren and Roni Frank in 2012, Talkspace raised $106.7 million to date.

Revolution Growth led the Series D. Existing investors Spark Capital, Norwest Venture Partners, Qumra Capital, Compound, and others.

Talkspace has a network of over 5,000 licensed therapists through a web platform and mobile app.
The company says Its platform has been used by over 1 million people across 10 countries but declined to provide revenue figures.

Users of the company are connected to a therapist to whom they can send unlimited messages using a monthly subscription service. They may use a messaging-only plan and options for live video sessions.

Talkspace also provides psychiatry services, including prescription fulfillment, and couples counseling.

In its press release, Talkspace said it would use the new funds “to accelerate the growth” of its commercial business. The company partners with employers, health plans, employee assistance programs (EAP) and educational organizations in an effort “to make therapy available and affordable.”

Talkspace has cooperation with Optum, a behavioral health business. It also provides services to employees via cooperation with Aetna, a CVS Health company, Magellan Health, New Directions Behavioral Health and others.

Talkspace claims its commercial business “now covers over five million lives.”

In addition, Talkspace said it plans to expand into two unidentified global markets.

Oren Frank told Crunchbase News that the company also plans to expand its artificial intelligence capabilities.

Currently, Talkspace’s data science team aggregates client and therapist interactions, enabling it to better match users “with the best possible therapists,”

“By studying a large corpus of successful treatment courses, we can apply large scale regressions, and build a decision-support system based on ML (machine-learning) models that help therapists better diagnose, use the appropriate interventions, understand whether their treatment plans are effective, and apply changes in real time,” he added.

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