Kinovati

Family caregivers carry enormous cognitive and emotional load — tracking medications, appointments, and symptoms while coordinating with relatives — and they burn out. Guidance is generic and scattered.

Delivering personalized, trustworthy caregiving guidance through natural language while keeping families coordinated, without overwhelming already-stretched caregivers.

• LLM-driven guidance engine grounded with RAG over vetted caregiving content.
• Family coordination layer for shared schedules, notes, and care events.
• Personalization based on the specific care situation and history.

1. 1Caregivers describe their situation in natural language.
2. 2The system returns personalized, grounded guidance and next steps.
3. 3Family members stay aligned through a shared care timeline.

• →Grounded generation to keep health guidance trustworthy.
• →Coordination-first design so the whole family shares the load.
• →Focus on burnout reduction as the core success metric.

The hardest part of caregiving AI is trust and coordination, not raw model capability — design has to earn confidence.

• Clinician-reviewed guidance library.
• Medication and appointment integrations.
• Pilot with real caregiving families.