Caspar AI Technology

Caspar’s generative AI uses data (such as motion, activity, and vitalsfrom ambient sensors to deliver 24/7 monitoring, personalized healthcare, and early escalation of potential health issues. Our multi-modal foundation model, trained on 150 billion data points, acts as a co-pilot for the staff, improving efficiency and empowering them to provide better patient care. 

Diverse Data Sources

Our AI ingests data from discreet ambient sensors as well as 10+ EHR platforms.

Ambient Intelligence

Our AI cloud adapts to individuals’ patterns of behavior, delivering personalized insights without the need for cameras or wearables.

Improved Outcomes

Care teams receive AI-assisted health insights & alerts to deliver better care more efficiently.

MultiModal GPT + Datapoints

Multi-Modal AI

Caspar’s multi-modal AI ingests large volumes of continuous data from ambient 3D sensors, analyzing every moment of patient vitals, movement and behaviors to build comprehensive whole-person models. Our agentic framework considers complex correlations and identifies long-term trends for interpretable health insights, leading to better health outcomes. 

Personalized Ambient Intelligence

With seven patents granted, our AI builds a comprehensive, patient-centric model based on each individual’s unique biometrics. Each patient’s baseline is like a fingerprint with countless variations, which makes analyzing trends too complex and difficult for a human being alone. With our AI co-pilot analyzing 10,000s of data points on-demand, care teams are able to use Caspar’s unique and valuable insights to provide the right care to those who need it most, when they need it.

Our solution is passive and does not require cameras or wearables, instead using existing passive contactless radar & wifi-based sensors to get vitals and 3D behavioral data. 

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Caspar ChatBot
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AI Co-Pilot for Care Workflows

Our AI detects 20 health & wellness markers, including sleep quality, cardiac & respiratory trends, bed exit/imminent fall, pressure scores, and restlessness. These insights and alerts are made available as an AI co-pilot into existing workflows like EHRs, apps and nurse call systems.

Our scores and alerts are easy for staff to interpret, allowing them to independently review the basis of our AI recommendations. Alerts are designed to auto-adapt to different environmental conditions, improving accuracy and reducing alert fatigue.

Care Team Collaboration for Better Outcomes

Our data-driven platform has already detected over 20,000 incidents/insights in facilities and homes across the US and and has helped staff reduced detection times significantly (up to 10X).

Caspar’s AI continues to train and improve over time with ongoing staff feedback across large populations, as well as from analyzing longitudinal trends for each individual over time.

LHBM Model

Let's talk about your goals

Your monitoring team gets relevant alerts, reducing alert fatigue while optimizing patient care.