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Ziva Health›AI Agents›Continuous Intelligence Agent
Agent 01 · Continuous Intelligence

Know who needs attention —
and why.

The Continuous Intelligence Agent reviews everything known about each patient and decides what changed, whether it matters and what should happen next. Its job is to reduce noise, not create more alerts.

Request a demoSee how it decides →
Robert K., 67
Hypertension · home BP cuff
Needs review
What changed
Systolic BP has averaged ~160 for 9 days. His personal baseline is ~130.
Why it matters
Still below the clinic's critical threshold of 180, but a sustained shift of +30 from his own normal. Readings are consistent, not a single spike.
Context
Reported no new symptoms. No missed medication logged.
Next action
Clinician review of BP plan this week. Care Agent to confirm medication adherence.
ApproveEditAssign
How it thinks

Three questions,
for every change, for every patient.

A threshold only tells you a number was crossed. Continuous Intelligence reads each change in context: against the patient's own history, the care team's rules and what's happened recently.

01
What changed?
A new reading, a lab result, a symptom report, a trend that's shifting, or an event such as an ED visit.
ExampleSystolic BP up from ~130 to ~160
→
02
Does it matter?
Is it sustained or short-lived? Is it outside this patient's normal? Does recent context explain it?
ExampleSustained for 9 days, +30 from baseline
→
03
What should happen next?
One clear state with an explanation and a suggested action, routed to the right place.
ExampleNeeds review · confirm adherence
What it evaluates

Everything available in.
One clear state out.

The agent works with whatever information is available for each patient and evaluates it against several layers of context, not just one cutoff.

Patient information
Vitals & RPM data
Labs
Wearables
Symptoms
Patient-reported information
Medicationswhere available
Hospital / ED eventsSoon
→
Evaluated against
Clinical thresholds
Organization & provider thresholds
Patient-specific thresholds
Personal baselines
Longitudinal trends
Recent patient context
→
Structured intelligence
High priority
Needs review
Clinical observation
No action
Explanation & reasoning
Suggested next action
Classification, not alerts

Every meaningful change
gets one of four states.

Only two of them interrupt a person.

Four-state classification · coming soonClinical Observation Mode · live
High priority
Human attention may be required now
Escalated right away to the right person, with the reason and a suggested next step.
Goes toCare team, now
Needs review
A meaningful change that deserves review
Not necessarily urgent, but a real shift from the patient's normal or a gap worth a clinician's look.
Goes toClinician review queue
Clinical observation
Ziva keeps watching
Ziva gathers more information where appropriate and suppresses repeat alerts until the picture is clear.
Goes toZiva + Care Agent
No action
Doesn't currently need the team
Logged and kept in the patient's history. Nobody is interrupted.
Goes toPatient record
In practice

Where threshold-only software
gets it wrong.

Three common situations. In each, a single cutoff either stays quiet when it shouldn't or interrupts someone when it doesn't need to.

1 · A meaningful shift below the critical line
Systolic BP, 30 days. Personal baseline ~130. The clinic's critical threshold is 180.
Systolic BPPersonal baselineCritical threshold
Threshold only
Nothing

Never reaches 180, so no alert fires.

Continuous Intelligence
Needs review

A sustained +30 from his own baseline.

Reasoning
Readings have been consistent for 9 days, not a single spike. Suggest a review of his BP plan and an adherence check.
2 · A one-day dip after poor sleep
HRV, 14 days. Night 9: under 5 hours of sleep.
HRV (ms)Personal baselineFixed alert line
Threshold only
Alert

Below the line for one day, so the provider is paged.

Continuous Intelligence
No action

Short-term volatility explained by sleep. Recovered the next day.

Reasoning
One night of short sleep, with HRV back near baseline within 24 hours. No pattern, so the provider isn't interrupted.
3 · A hospital event
An ED visit is reported through a data partner. Hospital event feeds · coming soon
Sat 11pm
EventED visit · shortness of breath
Sat 11pm
IntelligenceHigh priority
Recognized as a meaningful event for a heart failure patient. Provider notified according to the organization's rules.
On discharge
Care AgentTransition workflow starts automatically
Event notice only
FYI

"Patient went to the hospital." Someone still has to decide what to do.

Continuous Intelligence
Act

The event triggers both the right notification and the follow-through.

See the transitions workflow →
Clinical Observation Mode Live

Not sure yet?
Ziva keeps watching.

Some changes need more information before anyone can tell whether they matter. Rather than alerting on every reading, Ziva places the patient in observation, gathers more data and holds back repeat alerts. When the picture is clear, it decides.

The clinical observation workflow →
Day 0
Observe
One elevated BP, no symptoms. "Observe for 3 days."
Days 1–3
Gather
The Care Agent requests repeat readings and asks about symptoms. Repeat alerts are held back.
Day 3
Decide
No actionif readings settle, or Needs review if the change persists.
Intelligence as infrastructure Deployment vision

Designed to work
outside Ziva, too.

Continuous Intelligence is being built so it doesn't need the full Ziva platform to run. An EHR, RPM platform, device company, health system, care management or virtual care platform could send it patient information. Ziva would return a structured state, the reasoning behind it and a suggested next action.

The plan is to deliver this through APIs, integrations and MCP where appropriate. It isn't available as a standalone service yet.

Your platform sendsreadings · labs · events · context
→
ZivaContinuous Intelligence
Illustrative response
// returned to the calling system { "patient_ref": "pt_8841", "state": "NEEDS_REVIEW", "what_changed": "Systolic BP ~160 for 9 days", "compared_to": { "personal_baseline": "~130", "org_threshold": "180" }, "reasoning": "Sustained shift from baseline; consistent readings; no symptoms.", "suggested_action": "Clinician review of BP plan; confirm medication adherence." }

Illustrative format only, not a published API.

Works with

When a decision needs more information,
the Care Agent goes and gets it.

Continuous Intelligence decides. The Care Agent follows through by requesting a repeat reading, checking a symptom or confirming a medication, then sends the answer back for re-evaluation.

Agent 02
Care Agent
Contact → ask → collect → remind → follow → document → escalate
How the Care Agent works →
Overview
How the two agents work together
Back to Ziva AI Agents →

See who needs attention
in your own patient panel.

We'll configure your thresholds and show how Continuous Intelligence handles a sample of your patients.

Request a demoExplore Ziva Agents →