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Detecting Subtle Signals

People exhibit clues about their state of mind in the way they talk, the words they use, and the facial expressions they make.

Observing these signals objectively —
and weaving them together, can offer evidence based insights about a person’s state-of-mind

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Introducing aiberry

aiberry is an AI-powered, multimodal platform that offers providers and care managers rapid, objective, and unbiased behavioral health assessments.

aiberry delivers evidence-based insights virtually (in telehealth scenarios) and at the point of care, offering unique outreach and scale opportunities.

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Our Mission

We can harness the power of AI by rapidly and accurately analyzing a patient’s text, voice and facial expressions to help providers identify a patient’s most important clinical needs.

By supporting providers with an objective, accurate, and scalable platform, they will be able to offer their expertise and care with greater efficiency and to more patients in need.

Today, those needs are greater than ever.

Our Origin Story

15 years ago, a group of professors and students at Oxford University and University of Paris hypothesized that depression could be detected by analyzing the unique muscles in our face. The hypothesis evolved to consider the insights available from voice and word context analysis.

Newton Howard, Soujanya Poria, and Navonil Majumder have spent the better part of the 2000s perfecting this science into a proven methodology for detecting depression and using science to help democratize mental wellbeing.

This methodology is the basis for aiberry’s patented AI and our inspiration for putting an impactful 21st century tool into the hands of behavioral health clinicians.

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Why Now

Behavioral health is the real pandemic of the 21st century and COVID-19 has only exacerbated this crisis. At the same time, this crisis has increased the adoption of tele-health services.

aiberry’s behavioral health screening platform sits at the intersection of these trends. The platform will benefit all cross-sections of the society, but especially will be useful for sections that are underserved and most vulnerable. Youth, women, uninsured, front-line workers and patients in rural areas will benefit the most from our innovation.

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Our Commitment

Our Machine Learning (ML) pipelines are designed to eliminate biases, including those related to age, gender, sexual orientation, and race.

As we learn more through our clinical trials, our algorithms will continue to improve.

Throughout, patient privacy is paramount.