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Gillie.AI for Home Care

Predictive Analytics Revolutionises Home Care

Artificial intelligence predicts changes in customers’ health and well-being

Artificial intelligence monitors the condition of customers in home care and helps care providers anticipate changes in the condition.

Artificial intelligence can detect weak signals of changes in the customer’s condition and use them to predict upcoming deviations. Early intervention in deviations improves customer well-being and reduces the need for care.


Live at home longer
Clients can live at home for an extended period of time!
Optimise your resources and costs
Allocates your limited care resources to those who really need it.
Reduces health care needs
Fewer hospital days? Less ambulance calls and on-call visits? Yes, it’s true.
Increases satisfaction
Seniors and family members in the home care service chain leave better reviews!
Automatic care assessment
Using AI, we analyse the customer’s wellbeing using patient data, measuring results, and care notes.
Deviation alerts
Alerts to any deviations in customer’s wellbeing.
Our virtual carer can learn what is normal for a patient in a matter of 2-3 weeks. AI does not alert of any irrelevant changes.
Customers ordered by priority
Our AI orders clients by the critical nature of their care. This is viewed in the order of the client’s pain or depression severity, for example.
Predicts changes and anticipates emergencies
Anticipates up to 50% of upcoming emergency visits for patients currently living at home.
Thorough assessment of customer ability to live at home
Using real time analysis, our AI estimates whether a patient can live at home. Our AI will alert you if it suggests a patient is unable to live at home for any longer.
Quality of life
Our AI assesses the quality of life of your clients and predicts if the existing quality could be improved.
Enables comparison of teams
An up-to-date and objective way to compare care teams.

What the solution is for?

Description of the solution


Clinical effectiveness

Costs and economic evaluation

Organisational aspects

Legal aspects