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ProtegeAi

AI-driven theft prevention turning raw detection data into actionable retail security

Role

Lead Product Designer

Year

2025

Company

ProtegeAi

Focus

AI Security Mobile FlutterFlow

Impact

<15s

Incident response time

Reduced shoplifting response from minutes to under 15 seconds

30%

Dev estimation reduced

FlutterFlow-optimized component library cut development time

1:1

Visual fidelity

Design-to-code parity ensured through platform-aligned components

The Challenge

Physical retailers lose billions annually to shrinkage, yet most security systems are reactive rather than proactive. ProtegeAi needed a mobile interface that could bridge the gap between AI detection and human intervention — a professional-grade security tool that felt as intuitive as a consumer app, allowing store managers to triage incidents instantly without technical training.

"We need a system that doesn't just watch; it alerts and guides the user to the exact moment an incident begins."

— Stakeholder

The Solution

A mobile-first platform focused on real-time triage and legal compliance. Drawing from benchmarking of Verkada and Ring, I implemented a neutral, high-trust visual language with high-contrast alerts.

verified

Incident Triaging

One-tap verification system (True/False) that validates AI detections in seconds.

gavel

Guided Compliance

Legal guardrails displaying reminders to agents before suspect interaction, mitigating corporate liability.

analytics

Analytics Dashboard

Complex security logs converted into actionable KPIs including resolution time and high-risk sectors.

Reflection

Designing specifically for the FlutterFlow ecosystem taught me that true UX excellence comes from understanding the medium. By aligning the design system with platform-specific widget logic early on, we eliminated the typical design-to-dev friction, resulting in a production-ready product in record time.

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