Transform health data into answers that improve care

AI can help to answer complex questions that lead to cost and time savings – if you get it right.

Employing AI is no longer a luxury, it’s a necessity

We are living in an era of data overload and burned-out clinicians. In healthcare, AI can equip patients and providers to understand health risks and improve outcomes at lower cost.

We build AI into our population health solutions. We make sense of massive amounts of data so healthcare organizations and providers can decide what is best for their patients, individuals can take control of their own health, and researchers can conduct more rigorous real-world evidence studies.

Who we help

ACOs, payers, and value-based care networks

Deploy a broad suite of predictors to improve patient outcomes, reduce excess cost, and inform contracting decisions.

Providers

Quickly scan patient health records and identify those who need additional attention and why.

Individuals

Take ownership of your health data with practical, personalized predictions and a curated health history through Health Picture, our free app.

Researchers

Enjoy the benefits of a cost-effective approach to large-scale research studies.

The HDAI difference

Bring individuals into focus

Old way

One size fits all

What is Michelle’s risk adjustment
factor (RAF)?

2.1

RAF score

1.00 is average

Single score

Based on generic calculator

Sample patient, Michelle F | age 73

Parkinson’s, hypertension,
tobacco user, no recent hospitalizations
or recent ER visits

HDAI

Personalized Population Health

How does Michelle compare to other women her age?

5.1x risk

of hypothyroidism
onset

2x risk

of dementia onset

1.5x risk

of mortality in next 90 days

2.5x risk

of hospitalization due to falls and infection

AND MORE:

Including predictions of adverse events, chronic condition onset, total cost, high-value procedures, specialty utilization and more.

Over 100 predictions/individual

The HDAI difference

Bring individuals into focus

Sample patient, Michelle F | age 73

Parkinson’s, hypertension, tobacco user, no recent hospitalizations or ER visits.
See how

Old way

One size fits all

What is Michelle’s risk adjustment
factor (RAF)?

2.1

RAF score

1.00 is average

Single score

Based on generic calculator

HDAI

Personalized Population Health

How does Michelle compare to other women her age?

5.1x risk

of hypothyroidism
onset

2x risk

of dementia onset

1.5x risk

Mortality in next 90 days

2.5x risk

of hospitalization due to falls and infection

AND MORE:

Including predictions of adverse events, chronic condition onset, total cost, high-value procedures, specialty utilization, and more.

Over 100 predictions/individual

Most AI companies take from providers and healthcare organizations—their data, their attention, their money. We are trying to give them something they sorely need: not just insight but time to look patients in the eye and have the right conversation with them.

Nassib Chamoun

Founder, President, & CEO