AI for Home Care Providers

Residential aged care runs from a single site: one reception line, nurse stations, and residents who are always on the premises. Home care is the opposite — a distributed workforce delivering visits in hundreds of private homes, coordinated from an office that clients, families and care workers all call at once. Our home care configuration is built around that reality: visit confirmations, automated welfare check-ins, missed-visit escalation and proactive family updates, rather than facility reception and admissions workflows. If your organisation operates residential facilities as well, we configure both side by side.

Yes. The AI identifies the caller type — from number recognition where the caller is known to your system, and from the conversation itself where they are not — and follows a different flow for each. Clients can confirm, reschedule or ask about their next visit. Family members receive only the information your consent settings permit for that client, and can leave feedback or raise concerns. Care workers can report running late, confirm arrival, or flag an issue at a visit, and those updates are logged against the roster. Anything urgent — a welfare concern, a fall, a worker unable to reach a client — is escalated immediately to your on-call coordinator rather than handled by the AI alone.

Yes. AI Healthcare provides API-based integration with the platforms Australian home care providers already use, including AlayaCare, ShiftCare, Turnpoint, Carelink+ and Visual Care. The integration reads visit schedules and client details so confirmations and check-ins always reflect the live roster, and writes call outcomes, check-in results and schedule-change requests back to the client record — no double data entry. Where a platform does not expose a suitable API, we set up structured export workflows instead. Your rostering system remains the source of truth; the AI handles the communication around it.

You configure a confirmation window for each visit type. If a visit is not confirmed as started within that window — from worker check-in data in your rostering platform, or from the worker calling the line — the AI acts: it contacts the care worker first, then places a welfare call to the client, and if either step raises a concern it alerts your on-call coordinator with the full context of who was called and what was said. Late-running visits follow a lighter version of the same chain. Every step is timestamped and logged, giving you a defensible record of how each visit exception was managed.

Consent is recorded per client, not per organisation. Where a client has a guardian, an enduring power of attorney, or a supported decision-making arrangement, that contact is flagged in the system as the relevant decision-maker, and information sharing follows the consent matrix you set for that client — who may receive schedule updates, who may be told about welfare concerns, and who may make changes. Clients keep the rights set out in the Statement of Rights under the Aged Care Act, and all handling of personal information remains subject to the Privacy Act 1988. We provide consent templates during onboarding to capture these settings at intake.

It does not replace your quality management system, but it feeds it. Every confirmation, check-in call, missed-visit escalation, family update and complaint capture is stored as a structured, timestamped record — exactly the kind of evidence of monitoring, communication and incident follow-up that the strengthened Aged Care Quality Standards ask registered providers to demonstrate, and that Aged Care Quality and Safety Commission audits look for. And because Support at Home caps care management at 10 per cent of each quarterly budget, coordinator time saved on routine calls means more of that capped allocation goes to actual care oversight.