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VRYT
VRYT
VRYT
(Verify it)
(Verify it)
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Industry
Fin-tech,
E- commerce
My Role
Product Designer
Conceptual Project
Deliverables
Brand Identity
Mobile App
Prototyping
Interactive Design
Project Overview
VRYT is a mobile app that helps online shoppers quickly verify suspicious links, check transaction status, and match confusing bank debits to the right order
Problem Statement
Problem Statement
Online shoppers receive delivery messages, payment alerts, and suspicious links with no easy way to verify if they’re genuine, while bank debits and order updates are scattered across multiple apps.
This creates a trust gap: users feel anxious, waste time cross‑checking information, and risk ignoring real updates or tapping unsafe links.
Online shoppers receive delivery messages, payment alerts, and suspicious links with no easy way to verify if they’re genuine, while bank debits and order updates are scattered across multiple apps.
This creates a trust gap: users feel anxious, waste time cross‑checking information, and risk ignoring real updates or tapping unsafe links.
The Solution:
The Solution:
VRYT acts as a verification layer between users and the messages they receive during online shopping.
VRYT acts as a verification layer between users and the messages they receive during online shopping.
Instead of expecting users to analyse every SMS or link, it gives them one place to check: “Is this safe, and what is this for?”
Instead of expecting users to analyse every SMS or link, it gives them one place to check: “Is this safe, and what is this for?”
From one conversation to a product idea
From one conversation to a product idea
I started this project after talking to a friend who regularly shops online and manages event-related deliveries. She often receives multiple SMS links, payment alerts, and unclear bank debits at the same time, which makes it hard to tell what is genuine and what needs attention.
I started this project after talking to a friend who regularly shops online and manages event-related deliveries. She often receives multiple SMS links, payment alerts, and unclear bank debits at the same time, which makes it hard to tell what is genuine and what needs attention.
That conversation helped me identify a simple but important trust gap in the e-commerce experience, and it became the starting point for VRYT.
That conversation helped me identify a simple but important trust gap in the e-commerce experience, and it became the starting point for VRYT.
To understand whether this was just my friend’s problem or part of a larger pattern, I first looked at reports and articles about delivery and payment scams to see how widespread the issue really is.
This helped me realise that her experience was not an isolated case, but part of a broader shift where fast e‑commerce and AI-generated phishing are creating new risks for everyday users.
To understand whether this was just my friend’s problem or part of a larger pattern, I first looked at reports and articles about delivery and payment scams to see how widespread the issue really is.
This helped me realise that her experience was not an isolated case, but part of a broader shift where fast e‑commerce and AI-generated phishing are creating new risks for everyday users.
I then ran a Google Forms survey with 30 active online shoppers and followed up with one‑on‑one conversations.
I then ran a Google Forms survey with 30 active online shoppers and followed up with one‑on‑one conversations.
Results
MY Survey
MY Survey
I then ran a Google Forms survey with 30 active online shoppers and followed up with one‑on‑one conversations.
To understand whether this was just my friend’s problem or part of a larger pattern, I first looked at reports and articles about delivery and payment scams to see how widespread the issue really is.
This helped me realise that her experience was not an isolated case, but part of a broader shift where fast e‑commerce and AI-generated phishing are creating new risks for everyday users.
Survey insight:
Survey insight:
Results
MY SURVEY
84% – Delivery anxiety
Users worry when delivery messages look unclear or suspicious.
84% – Delivery anxiety
Users worry when delivery messages look unclear or suspicious.
62% – Payment confusion
Users struggle to identify which bank debit matches which order.
62% – Payment confusion
Users struggle to identify which bank debit matches which order.
4.2 apps – Context-switching fatigue
Users keep jumping between apps to track orders and payments.
4.2 apps – Context-switching fatigue
Users keep jumping between apps to track orders and payments.
70% – AI scam concern
Users are worried about fake links and AI-generated scams.
70% – AI scam concern
Users are worried about fake links and AI-generated scams.
84% – Delivery anxiety
Users worry when delivery messages look unclear or suspicious.
62% – Payment confusion
Users struggle to identify which bank debit matches which order.
4.2 apps – Context-switching fatigue
Users keep jumping between apps to track orders and payments.
70% – AI scam concern
Users are worried about fake links and AI-generated scams.
Goals of VRYT:
Goals of VRYT:
Reduce user anxiety by making suspicious links and messages easy to verify
Reduce user anxiety by making suspicious links and messages easy to verify
Reduce user anxiety by making suspicious links and messages easy to verify
Turn confusing payment data into clear order information.
Turn confusing payment data into clear order information.
Turn confusing payment data into clear order information.
Keep security and order updates in one calm, easy-to-use place.
Keep security and order updates in one calm, easy-to-use place.
Keep security and order updates in one calm, easy-to-use place.
Blueprint for VRYT :
Blueprint for VRYT :
Visual Identity: The VRYT Dynamic Loader
Visual Identity: The VRYT Dynamic Loader
Thread Detected
Thread Detected
Safe Status
Safe Status
System Trigger ➔ Gray/Neutral State (Active Ledger Query)
Threat Detected ➔ Crimson/Red Glow (Immediate Danger Isolation)
Safe Status ➔ Emerald/Green Glow (Verified Transaction Match)
System Trigger ➔ Gray/Neutral State (Active Ledger Query)
Threat Detected ➔ Crimson/Red Glow (Immediate Danger Isolation)
Safe Status ➔ Emerald/Green Glow (Verified Transaction Match)
System Trigger ➔ Gray/Neutral State (Active Ledger Query)
Threat Detected ➔ Crimson/Red Glow (Immediate Danger Isolation)
Safe Status ➔ Emerald/Green Glow (Verified Transaction Match)
My Learnings
My Learnings
Designing for edge cases is as important as the primary flow.
Designing for edge cases is as important as the primary flow.
Designing for edge cases is as important as the primary flow.
Trust must be visible, not assumed.
Trust must be visible, not assumed.
Trust must be visible, not assumed.
Product decisions should balance automation with user control.
Product decisions should balance automation with user control.
Product decisions should balance automation with user control.
Iteration creates better products then first ideas.
Iteration creates better products then first ideas.
Iteration creates better products then first ideas.
Future Evolution
Future Evolution
Cross-device sync (Keep scan history and alerts synchronized across devices).
Cross-device sync (Keep scan history and alerts synchronized across devices).
Cross-device sync (Keep scan history and alerts synchronized across devices).
Smarter auto scan ( Detect and prioritize newly copied links automatically).
Smarter auto scan ( Detect and prioritize newly copied links automatically).
Smarter auto scan ( Detect and prioritize newly copied links automatically).
AI scam explanations (Explain why link is flagged, not just the results).
AI scam explanations (Explain why link is flagged, not just the results).
AI scam explanations (Explain why link is flagged, not just the results).
