A steady voice during recovery, wherever home is.
Olive calls people recovering at home after surgery or cancer treatment, especially in regional and remote communities, asking about pain, wounds, side-effects and mood, then routing any concern to a real clinician, fast.
The riskiest window has the least contact
After surgery or cancer treatment, people go home to communities that can be hours from the treating hospital. A wound infection, sepsis, a clot, a chemo fever or recurrence-related distress can escalate unnoticed between scheduled visits.
It falls hardest on people recovering at home in rural and remote areas
Distance amplifies the same problem: less easy access to a GP, a longer trip to the nearest emergency department, and a longer wait before a worsening symptom is seen by anyone.
The standard exists; the daily contact does not
NSQHS Standard 8, Recognising and Responding to Acute Deterioration, sets the expectation inside hospital walls. Once someone goes home, that structured watch usually stops at the front door.
Australian Commission on Safety and Quality in Health CareThree moments between discharge and a return visit.
No app. No screen. Just a phone call paced for someone who is recovering, wherever they live.
Scheduled Recovery Calls
Olive calls on a clinician-set schedule after discharge from surgery or cancer treatment such as chemotherapy or radiotherapy. No app, no screen: a plain conversation, paced gently for someone who is recovering.
Listening for Red Flags
Olive asks about pain, the wound or treatment site, breathing, and how side-effects like nausea, fatigue or appetite are tracking, with built-in safeguarding for wound infection, chemo fever, clot symptoms and recurrence-related distress.
Fast, Structured Escalation
Anything concerning is captured, scored and routed to the treating team or an on-call clinician straight away, not left in a form nobody reads until the next visit.
Built for the distance between visits.
Recovery continues long after discharge. Olive keeps regular contact between appointments, for people recovering, their families, and clinicians.
Post-surgical recovery
Wound, pain and mobility check-ins in the weeks following an operation, at home rather than in a waiting room.
Post-treatment oncology follow-up
Check-ins after chemotherapy or radiotherapy, watching for neutropenic fever, treatment side-effects and recurrence-related distress.
Rural and remote communities
Built for people who live hours from the treating hospital, where deterioration is most likely to go unnoticed between visits.
Deterioration between visits
A structured early-warning layer that complements ward follow-up and discharge planning, not headcount to replace it.
Family carers
Family stay informed on recovery without becoming the monitoring system themselves.
Research partners
Patient-reported recovery outcomes at scale, for organisations studying deterioration and readmission in rural and remote cohorts.
Two ways to work with us.
We are talking with health services and research groups about what a first, small, carefully scoped pilot could look like.
Health service pilot
Scheduled recovery check-in calls for a defined post-surgical or post-treatment cohort, escalating into your existing clinical governance and on-call pathways.
Research partnership
Patient-reported recovery outcomes, captured by voice, for research into deterioration and avoidable readmission in rural and remote cohorts.
Built on the same principles as our aged-care pilot.
Aligned with the Rome Call for AI Ethics, the CTECH Statement (Boston College, March 2026), and the CHA Code of Ethical Standards.
Every call opens with disclosure
“Hello, it’s Olive, an AI companion for recovery after treatment, not a doctor or nurse. If you need urgent help, please call triple zero.” The same AI disclosure used across all careplans AI companions, word for word: Olive always says she is an AI.
Australian data residency, by design
Australian data residency is a design priority for the Olive pilot, to be finalised against the treating health service’s data-residency requirements before any live cohort is enrolled.
Human-in-the-loop, always
Olive never diagnoses, never names a specific medication, and never speculates on whether a treatment worked or a cancer has returned. Every red flag is routed to the treating team; the clinician decides.
Aligned to Vatican · CTECH · CHA ethics
Built on the Rome Call for AI Ethics, the CTECH Statement (Boston College, 2026), and the CHA Code of Ethical Standards. Same ethical foundation as our aged-care pilot.
Kate is the coordination engine behind every careplans AI voice companion.
Kate schedules the calls, guides the conversation, and turns what is heard into actions for your care team, making every call purposeful, every insight actionable, and every outcome measurable. Kate is the reason this is more than an AI that makes phone calls.
What Kate does on every call
- Schedules the call at the right time for each person
- Selects the right voice companion for the program (for example Mary for aged care wellbeing, or Bloom for new parents)
- Loads full context from every previous conversation
- Configures the conversational pathway with branching logic, conditions, and guard rails
- Orchestrates the conversation in real time
- Receives emotional signals so the conversation adapts to mood in real time
- Triggers mid-call API actions: check a database, book an appointment, update a CRM record, send an SMS
- All while the person is still on the line
- Transcription and recording
- Routine analysis on cost-optimised local models
- Advanced reasoning through frontier models
- Emotional analysis (tone, sentiment, mood)
- Generates WHO-5 wellbeing scores, structured JSON data, and compliance evidence
What makes Kate different
Escalation and action
Escalation alerts to the care team. Family notifications through nonni.ai. CRM updates. Webhook pushes. Compliance evidence packs. Follow-up call scheduling.
Longitudinal intelligence
Kate maintains memory across calls. It tracks wellbeing trends over weeks and months. It detects a gradual mood decline over three weeks, increasing mentions of pain, growing isolation.
Multi-model architecture
The right model for each task. Routine analysis on cost-optimised local models. Advanced reasoning through frontier models. Emotional analysis through specialised voice models. Cost-optimised without compromising accuracy.
Cross-call memory
Every voice companion remembers. Margaret mentioned her daughter last Tuesday. John has been sleeping poorly for two weeks. Context carries forward automatically.
Conversational pathways
Node-based conversation flows with branching logic, conditions, and guard rails. The AI follows the pathway. Hallucination-proof. Safe by design.
Continuous compliance
Every call maps to the relevant quality standards. Evidence generates as a byproduct of caring, not as an admin task. Always audit-ready.
Help us pilot Olive.
We are looking for one health service ready to trial a small, carefully scoped post-surgical or post-treatment recovery cohort, ideally in a rural or remote setting, where the gap between visits is greatest.
Talk to Us About a PilotOr email us directly at info@careplans.io