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Case study 02 · Mobile app

Faster help, trusted information. A safety app for India's everyday emergencies.

Role
Sole UX Designer
Company
Tejis.ai
Platform
Android
Team
AI team, mobile devs, stakeholders
Status
Production-ready, 8 test builds

In 30 seconds

The starting point

When something dangerous happens nearby in India, most people call someone. They post on WhatsApp. They hope someone sees it. There is no fast, central place to report what is happening, get help or find information you can trust.

Citizen App was built to change that: a hyperlocal safety platform where people report incidents in real time, trigger SOS alerts and stay informed with verified local news. I was the sole UX designer. Requirements and initial research came from the Head of AI. My job was to turn them into a clear, usable, trustworthy experience, working closely with the AI team, the mobile developers and the stakeholders.

Module 1: reporting an incident

The hard part: the person filling this form is stressed, scared or in danger. My first version put everything on one long screen. The team flagged it immediately, and they were right. To a person who just witnessed an accident, a long form is not a tool. It is an obstacle.

So I broke it into steps, one question per screen. What happened? How urgent is it? Add details. Review. Submit. Each screen asks one thing a stressed person can actually answer.

Visual: the single-screen v1 next to the final step-by-step flow

Module 2: a feed you can trust

The feed mixes citizen reports with verified news. My first instinct was to separate them into tabs, because they carry different levels of trust. I designed it that way twice. Then the investor pushed back and asked for one mixed feed. That was a real business constraint, and the direction changed.

But the trust problem did not go away just because the tabs did. So I moved the trust signal onto every card instead. Each post carries a badge showing exactly where it stands: under review, verified, approved or not approved. Once the AI confirms a report, the badge updates on its own. Users always know what they are reading.

When I could not control the structure, I controlled the signals.

Honestly, the badge system solved the problem better than the tabs would have. It was appreciated by stakeholders, and it kept the feed dense without making it misleading.

Visual: feed iterations v1 to v4, with the verification badges

Module 3: SOS, the highest-stakes flow in the app

A person triggering SOS may be panicking, injured or in danger. Every extra tap and every unclear label has a cost. The first version had a plain SOS button. One tap, alert sent. The gap: a medical emergency and a fire need different responders, and a generic alert gives them nothing to act on. But adding an extra screen to pick the type felt wrong too.

The answer was to put the emergency type inside the gesture itself. Swipe up for a medical emergency. Swipe down for anything else. Zero extra screens, zero extra taps, and the responder still gets the context they need.

Visual: the swipe-based SOS trigger and the countdown screen

Module 4: the map, and the feature I proposed myself

A safety map has to answer two different questions. What is happening right now? And which areas are dangerous over time? One dropdown switches between the two: an incident view with markers for live events, and a hotspot layer that turns the map into a heat map of the last three months. Tapping a hotspot shows an AI summary in plain language: "45 incidents in 3 months: 20 accidents, 15 fires, 10 floods." Insight, not just data.

The bigger idea came from watching how people actually think about safety in India. It is rarely just personal. A mother worries about her daughter's commute. A husband checks if his wife reached home. I proposed putting family members on the same map as the incidents, so you see where your people are and what is happening around them in one view. That proposal reframed the app from a personal safety tool into a family safety platform.

The Family Safety Network was fully designed and prototyped, then cut from the first release for time. It remains ready for a future version.

Visual: incident view, hotspot heat map, and the family drawer

Module 5: an AI legal advisor for people who never had one

Most people in India do not know their basic rights. What can a police officer ask of you? What documents must you carry? The feature had to make legal help feel possible for someone who has never spoken to a lawyer and would not know how to start.

An empty chat box is intimidating, so the screen opens with topic chips: Traffic Rules, Police and Arrest Rights, Women's Rights, Cyber Fraud, Workplace Rights, Consumer Rights. Tap one and the conversation starts. The voice mode shows an example before you speak: "Say something like: What are my rights if police stop me?" That one line teaches people how to ask.

Module 6: a profile that closes the loop

Most profile pages are settings pages in disguise. This one tracks outcomes. Every report a user submits goes through verification, and My Reports shows exactly where each one stands, with a notification badge when something changes. Badges show what you did and when, and unearned ones show a progress bar toward unlocking them. Contribution you can see, not just a points total.

The result

What I learned

The honest lesson: a good design decision, backed by data and logic, can still be overruled by seniority. The feed tabs were the right call and they still got cut. The skill is not only making the right decision. It is finding a way to serve users inside the constraints you are given. The badge system was my answer to that.

The SOS module taught me how to design for panic: not what users need, but what they are capable of doing under extreme stress. I will carry that into every project.

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