Turn wearable health data into early warning alerts

Analyzes wearable health data for risk signs and automatically sends alerts and schedules follow-ups when needed.

How the work actually flows

It branches. Exactly one path is taken; runs once per each monitored person's data stream.

Pattern: Exclusive Choice (4) · Multiple Instances with a priori Design-Time Knowledge (13)

flowchart TD trig>"new wearable reading arrives"]:::trig s0["standardize wearable data"]:::task s1[["calculate risk score"]]:::mi s2["compare to historical trends"]:::task trig --> s0 s0 -->|"one per each monitored person's data stream"| s1 s1 --> s2 gx{"× risk threshold crossed"}:::gate s2 --> gx p00["send alert email"]:::task gx -->|"threshold crossed"| p00 p01["schedule follow up"]:::task p00 --> p01 p10["no action taken"]:::task gx -->|"normal reading"| p10 p01 --> out p10 --> out out[/"risk scored alerts and follow ups"/]:::out pay{{"catches health risks before emergencies"}}:::pay out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepRuns once per itemOne path onlyResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsKnowledge Base & RAGEmail AutomationMessaging & NotificationsSpreadsheet & Database OpsScheduling & Calendar
Connects
OpenAIGoogle CalendarMongoDBPostgreSQL
Featured in

The problem it solves

Reviewing wearable health data for warning signs takes constant attention that no care team can realistically give every patient, every day. Subtle changes that signal a real problem can go unnoticed until it becomes an emergency.

Who it fits

Clinics, corporate wellness programs, or care teams monitoring patients or employees through wearable devices.

How it works

  1. Wearable device data streams in continuously and is standardized
  2. AI analyzes the trends and calculates a risk score for each person
  3. Current readings are compared against historical patterns to catch anomalies
  4. When a threshold is crossed, an alert goes out by email and a follow-up is scheduled automatically
What you get

Health scares you catch before they escalate

People being monitored get flagged early when their wearable data shows a real warning sign.

What you get

Risk-scored health alerts and automatically scheduled follow-up appointments.

What you need

A wearable device data feed, a database, an OpenAI API key, email, and a Google Calendar account.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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