Saahas
Where Safety Isn’t Silent — It’s Shared.
The problem Saahas solves
💡 The Problem It Solves
The 1st Ever Safety Platform Where He & She Co-Create Safer Streets. Safety is often reactive, gender-biased, and inconsistent.
Women, non-binary individuals, and allies often lack trusted, real-time information about the safety of their surroundings — and even when they report, their voices are often lost in unverified noise.
There’s also no structured, accountable way for men to step up — leading to a culture of silent bystanders, not active allies.
Traditional safety tools focus only on alerts or panic buttons — not on building a verified, inclusive, and proactive safety ecosystem including heatmaps.
🛠️ What Our App Solves —
🗺️ Crowdsourced + AI-Verified Safety Heatmap
A dynamic heatmap created by the community, for the community.
🚨 Smart Precaution Methods
Rather than waiting for harm, we enable prevention through awareness:
- Location Alerts when users enter risky zones (based on heatmap data)
- Route Planning to suggest safer alternatives
- SOS Button + Ally Network for instant support
- Weekly Informative Updates on safety laws, self-defense tips, and gender empathy
Gender-Inclusive & Role-Specific Engagement
- We designed the app with dual-role logic: He / She
- Both roles interact through shared maps, reports, and trust-building challenges — breaking silos.
- Safety becomes shared, not segregated.
💬 AI-Powered Pledge System
Every user begins with a personalized pledge, generated using GPT:
- Based on role, context, and behavior.
- Helps build self-awareness and emotional responsibility
- Adds to trust score and badge system — gamifying growth
🚀 Why It Matters
This isn’t just an app. It’s a social contract — rebuilt through code, community, and courage.
We’re bringing trust back into gender dynamics, and building a safety system where:
Everyone contributes
Everyone is accountable
And safety is no longer a gendered privilege, but a shared promise.
Challenges we ran into
Real-Time Heatmap Accuracy
One major hurdle was making the safety heatmap truly useful. With crowd-sourced reports coming in with varying reliability, we had to implement a decay system, trust-based weighting, and AI-assisted tagging to ensure only relevant and verified data influenced the heatmap. This ensured the map stayed accurate and actionable.
Anonymous Yet Accountable Users
Allowing anonymous usage while preventing misuse was a tough balance. We addressed this by generating unique device fingerprints to track behavior, while also offering Aadhaar verification as an optional trust booster—giving users a way to build credibility without sacrificing privacy.
GPT Integration with Dynamic Prompts
Generating relevant and personalized pledges using GPT was challenging. Static text felt impersonal, so we built a dynamic prompt system that adapted to user actions, roles, and locations—resulting in more meaningful and engaging experiences.
Designing the Trust Score
Creating a trust score that felt fair and motivating was harder than expected. We structured it around user activity—reporting, verifying, pledging, and reflecting—so each action contributed to progress through trust levels like New, Active, and Trusted Ally.
Reliable Background Functionality
Key features like SOS alerts and location-based prompts needed to work even when the app wasn’t active. To achieve this, we integrated Android’s IntentService, ensuring critical safety tasks could run in the background reliably.
Final APK Build Hurdles
Converting the project into a stable APK was unexpectedly difficult. We ran into issues with build failures, permissions, and package conflicts. Switching to EAS Build and manually resolving dependencies allowed us to finally package and test the app successfully under pressure.
Tracks Applied (2)
Best use of Gemini API
Major League Hacking
Best Use of MongoDB Atlas
Major League Hacking