Calm-E: From Wait to Care

Inspiration

Ever left the doctor’s office feeling more confused than reassured? Calm-E was inspired by this all-too-common experience around emergency room, aiming to transform uncertainty and long waits into clarity and confidence. Too often, patients walk away with lingering uncertainty, unsure about the necessity behind tests, treatments, or procedures—or simply feeling fear or anxiety because they don’t fully understand what these entail. This lack of transparency and communication is a key challenge in healthcare today. Calm-E aims to bridge that gap, offering patients clear insights into their medical journey, and providing transparency into the doctor's perspective. Our goal is to make healthcare more accessible, understandable, and ultimately, more comforting for all.

What it does

Calm-E is designed to simplify the healthcare experience and provide patients with clarity during every step of their medical journey. By addressing patient concerns before and after their doctor visit, Our innovative platform operates in two key phases:

Before the Doctor's Visit: While in the waiting room, our AI companion engages with patients by first helping them input their symptoms and providing insights into potential causes. Calm-E then offers tailored information on what to expect during their visit, prepares them for questions doctors might ask, and provides personalized support through meditations, distractions, or simply being a listening ear.
After the Doctor's Visit: Calm-E continues to support patients by clarifying the reasoning behind their prescribed tests, treatments, or surgeries. It explains the doctor’s thought process and supplements it with relevant medical knowledge, helping patients gain a deeper understanding of their condition and treatment plan. This ensures transparency, peace of mind, and empowers patients to take an active role in their healthcare journey. By combining education, support, and personalized care, Calm-E transforms the patient experience, turning waiting rooms into opportunities for clarity, comfort, and preparation.

How we built it

We developed the frontend using Next.js and Tailwind CSS. The backend, built with TypeScript, integrates with Google Cloud Vertex AI and Gemini APIs to power the chatbot’s responses. Structured prompts were fine-tuned, designed to adapt dynamically to different patient interactions. React components were used to ensure modularity and maintainability.

Challenges we ran into

One of the biggest challenges was designing an AI-powered system that delivers accurate and empathetic responses. Fine-tuning prompts to handle diverse patient scenarios required significant effort. Additionally, integrating the Google Cloud Vertex AI API presented technical hurdles, as we had to ensure compatibility with our backend setup.

Accomplishments that we're proud of

We're incredibly proud of successfully building a fully functioning chatbot that tackles a critical and common real-life challenge, one that has long lacked effective solutions. Seeing all the components—frontend, backend, and AI logic—come together into a polished product is a testament to our teamwork and problem-solving skills.

What we learned

This project taught us a lot about combining advanced AI with user-centric design. We gained a deeper understanding of integrating AI into solutions and how to structure effective prompts for AI models. Some of our team members also learned React and Next.js for the first time, which was an exciting challenge. Beyond technical skills, we improved our collaboration and time management, ensuring we stayed aligned on goals and delivered a working product.

What's next for Calm-E: From Wait to Care

We aim to expand Calm-E’s functionality further. One idea is to introduce a community board system where patients can share posts about their conditions. This feature would allow users to connect on a personal level, aligning their experiences with others facing similar challenges.