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Anvika Banner
About the Project
Inspiration
Women's health apps have existed for years, but most of them act as digital calendars, they record dates but rarely help users truly understand their bodies.
We wanted to build something more meaningful.
Anvika was inspired by the idea that every menstrual cycle is unique. Instead of giving generic predictions, we envisioned an AI-powered companion that learns from each user's cycle, symptoms, mood, sleep, lifestyle, and habits to provide personalized insights while keeping privacy at the center.
Our goal was to make menstrual health tracking smarter, more accessible, and more empowering.
What it does
Anvika is an AI-powered women's health companion that helps users:
- Track menstrual cycles and symptoms
- Log mood, energy, sleep, exercise, hydration, and nutrition
- Predict upcoming periods and fertile windows
- Generate personalized AI-powered health insights
- Visualize health trends over time
- Store personal data securely on-device
Rather than simply showing dates on a calendar, Anvika helps users understand how lifestyle choices influence their menstrual health.
How we built it
The application was developed using Flutter, allowing us to build a smooth cross-platform mobile experience.
Our stack includes:
- Flutter
- Dart
- Firebase Authentication
- DriftSQL Database (offline-first local storage)
- Gemini AI API for personalized insights
- Material 3 UI
The prediction engine combines historical cycle data with user-generated health logs to provide increasingly personalized recommendations as more data is collected.
Challenges we ran into
One of the biggest challenges was balancing personalization with user privacy.
We wanted AI-generated insights without requiring users to constantly upload sensitive health information to external servers. Designing an architecture that supports offline storage while still providing intelligent recommendations required careful planning.
Another challenge was handling limited historical data. New users often have little or no cycle history, making early predictions difficult. We addressed this by gradually improving prediction confidence as more logs are added over time.
Creating an intuitive interface for logging health information without overwhelming users was another significant design challenge.
Accomplishments that we're proud of
- Built a clean, intuitive women's health application from scratch.
- Designed an offline-first architecture using DriftSQL .
- Integrated AI to generate personalized health insights.
- Developed a privacy-focused experience where users control their own health data.
- Created a scalable foundation for future AI-powered health features.
What we learned
Building Anvika taught us that healthcare products require much more than technical implementation.
We learned the importance of user trust, data privacy, thoughtful UX, and responsible AI. We also gained valuable experience integrating Flutter, Firebase, local databases, and generative AI into a real-world application.
Most importantly, we learned that meaningful health technology should empower users rather than simply collect data.
What's next for Anvika
Our roadmap includes:
- Smarter AI predictions using long-term health patterns
- Personalized nutrition and fitness recommendations
- Wearable device integration
- Symptom trend analysis
- Doctor-ready health reports
- Medication reminders
- Anonymous community insights
- Enhanced privacy controls and secure cloud backup
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