Klava Innovation develops Quitoxil®, a medical device application that utilizes artificial intelligence to deliver personalized cognitive-behavioral therapy for individuals struggling with addictions. The platform addresses the high rates of therapeutic neglect in addiction treatment by providing evidence-based support and a confidential community for users seeking to overcome their dependencies.
Funding
$1.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Addiction treatment faces significant challenges due to high rates of therapeutic neglect, leading to relapse and impacting millions of lives globally. Traditional methods often lack personalized support and continuous engagement, resulting in low success rates for individuals trying to overcome dependencies such as smoking, alcohol, or other substances.
Solution
Klava Innovation offers Quitoxil®, a digital therapeutic (DTx) medical device application that delivers personalized cognitive-behavioral therapy (CBT) for addiction recovery. By integrating artificial intelligence, Quitoxil® tailors therapeutic strategies to each user, providing support to manage anxiety, understand addiction triggers, and prevent relapse. The platform extends the reach of healthcare professionals by offering continuous, evidence-based support and a confidential community, directly accessible via smartphone. Quitoxil® aims to reinforce motivation and abstinence, serving as a digital companion that complements traditional medical consultations.
Target Audience
Quitoxil® primarily targets individuals seeking to overcome addictions, such as smoking, and healthcare professionals in the field of addictology looking to enhance patient care with digital therapeutics.
Features
- Personalized cognitive-behavioral therapy (CBT) delivered via a smartphone application
- AI-driven algorithms that tailor therapeutic strategies based on individual user data
- Facial expression recognition for early detection of potential relapse
- Integration of evidence-based studies for addictive disorders
- Confidential community support for users in addiction recovery
- Data transmission to healthcare providers for informed medical follow-up