Building cutting edge technology for mental health - the right way
We build innovative AI algorithms to help measure mental health. Because we are entrusted with very sensitive, personal data, we prioritize data security and AI fairness. We are committed to researching and refining our technology with diverse groups of people to ensure our tools can support earlier detection and better outcomes for all.
Our AI
Clairity AI is our proprietary model that analyzes speech to help measure mental health risk. Our model is based on more than 10 years of clinical research on natural language processing (NLP) and machine learning (ML) algorithms. These studies showed that there are suicidal “thought markers” that cause changes in speech, which can be detected and measured with AI.
Data Security & Privacy
Our AI models analyze client/patient speech to identify vocal biomarkers for mental health risk. To do this, voice samples are securely recorded, transmitted to a HIPAA compliant cloud server, and analyzed by our patented AI models. Because we are entrusted with very sensitive, personal data, we prioritize data security and ensure data remains encrypted in transit and at rest.
Removing Bias and Constantly Improving
AI models identify patterns based on training data. Bias can find its way into AI models if the training sample is skewed. For example, if a group of people were over- or underrepresented in the sample, or if their data was collected during unusual circumstances (such as during a pandemic). Our researchers are continuously verifying that our models are not biased based on demographics, environmental conditions, timing, or other factors. We recently were awarded a grant from the NIH to support this ongoing commitment to ensure our models can support better outcomes for all.
What's Next
In addition to our validated suicidal risk identification model, we are preparing to release a depression model, and building anxiety and trauma models.
Suicidal risk identification model has been proven across therapeutic settings
