KomeKare

Inspiration

Cleo has done work with palliative care patients and noticed a clear separation between caregivers and doctors. Once patients leave clinical care, families are left to manage everything with little guidance or structure. We looked through forums and research and saw the same issue everywhere. Caregiving is disorganized, communication is weak, and important health details get lost, especially for chronic conditions like arthritis. This gap became the core problem we wanted to solve.

What it does

KomeKare is a mobile app that helps families manage caregiving in one place. Users can log symptoms, medications, and daily tasks. The app uses AI to detect patterns, flag risks, and generate simple doctor ready summaries. This makes it easier for doctors to understand what is happening between visits while reducing mistakes and stress for caregivers.

How we built it

We built KomeKare using React Native with Expo for cross platform development and Firebase for backend services like authentication and real time data syncing. We integrated AI to analyze structured health logs and generate insights. The focus was on keeping the interface simple and accessible, especially for older users and families under stress.

Challenges we ran into

One major challenge was trying to build too many features at once. It made the app harder to use and harder to present clearly. We had to cut down to the most impactful features. Another challenge was making the AI actually useful. Basic summaries were not enough, so we focused on structuring the data in a way that leads to meaningful insights instead of generic output.

Accomplishments that we're proud of

We built a working prototype that solves a real world problem. We created a system that not only tracks data but turns it into something useful for doctors. We also designed the app to be simple enough for everyday families to use, which is critical in high stress caregiving situations.

What we learned

We learned that good healthcare technology is about reducing friction, not adding complexity. Clear communication and structured data matter more than having a lot of features. We also learned how important it is to validate ideas with real world problems and feedback.

What's next for KomeKare

Next, we want to improve the AI to make predictions more accurate and personalized. We also plan to explore secure integrations with healthcare providers and expand features that support caregiver collaboration. Long term, KomeKare could help reduce hospital readmissions and improve overall patient care at home.