Inspiration

We wanted a women‑first fitness app built around our bodies and health. When you search for workout or wellness advice, it’s usually tailored to men or treated as one‑size‑fits‑all. That gap leaves too many women without guidance that reflects their real physiology. We set out to build a product that centers women’s rhythms and needs, not just averages.

What it does

Elara is a women‑first fitness and nutrition app that personalizes plans around your body and rhythm. Users sign up, complete a quick onboarding profile (goals, equipment, dietary needs, optional cycle tracking), and receive an AI‑generated daily plan with workouts, meals, and an insight explaining the “why.” The dashboard lets you submit a daily check‑in (energy, mood, symptoms) to refresh your plan, and you can update your profile anytime to keep recommendations aligned.

How we built it

We built Elara using React + Vite for the frontend and Node.js + Express for the backend with MongoDB as the database. We also used Gemini API to generate the structured workout and nutrition plans.

Challenges we ran into

A challenge we faced was narrowing the idea so we could finish a polished, working product within the hackathon timeframe. We also had to design the experience to be inclusive for all women, not just those who track their cycle, so the app still feels valuable even without cycle‑based inputs.

Accomplishments that we're proud of

We're proud of building a women‑first experience that’s inclusive by design, acknowledging different bodies, rhythms, and needs instead of a one‑size‑fits‑all approach. We're also proud of building a complete, working web app end‑to‑end—authentication, onboarding, AI‑powered plans, and daily check‑ins—all within the hackathon timeline.

What we learned

We worked with MongoDB for the first time and set up real data models and persistence. We also integrated the Gemini API and learned how important it is to enforce structured outputs so the UI can render plans reliably.

What's next for Elara

Next, we plan to implement a history view so users can see past days: previous plans, check‑ins, and trends over time. This will make progress visible and help users spot patterns across their cycle and energy levels. We’ll also explore simple insights based on that history to keep plans improving.