Fraudly.app VS Diffyn

Fraudly.app's answer

Fraudly doesn't rely on a single blacklist or database. It combines reputation data, security signals, reviews, domain intelligence, and scam indicators to help users identify suspicious websites quickly and confidently.

Diffyn's answer:

Addresses workflow and change management on LLM prompts, provide teams with traceability and visualization of tests across multiple models, provide deeper understading into efficiency of these prompts.

Fraudly.app's answer

Fraudly goes beyond basic URL checks by combining reputation data, reviews, security signals, and scam indicators into one clear trust score. We focus on simplicity, transparency, and helping everyday users stay safe online.

Diffyn's answer:

Diffyn is the platform that specializes on both change management and multi-model analysis.

Fraudly.app's answer

Fraudly is built using a modern web and mobile technology stack designed for performance, scalability, and reliability.

Core technologies include:

• Next.js and React for the web application
• TypeScript for type-safe development
• PostgreSQL for data storage
• Prisma as the database ORM
• Vercel for hosting and deployment
• SwiftUI for the native iOS application
• AI-assisted development to accelerate product innovation and iteration

Fraudly also integrates multiple external reputation, security, and scam-intelligence sources to analyze websites and provide trust and risk insights to users in real time.

Diffyn's answer:

React, Next.js, POSTGRESQL

Fraudly.app's answer

Fraudly is built for anyone who wants to know whether a website can be trusted. Whether you're shopping online, clicking a link from an email, verifying a new website, or helping family members stay safe online, Fraudly provides a simple way to assess trust before you act.

Diffyn's answer:

Professionals incorporating LLMs or AI tools in their workflow and wants to keep track of changes and test their prompts.

Fraudly.app's answer

Fraudly started with a simple observation: scam websites are becoming increasingly difficult to recognize.

Every day, people receive messages, advertisements, and links that appear legitimate at first glance. Modern scam websites often look professional, use HTTPS, display reviews, and imitate trusted brands, making it difficult for the average person to know who to trust online.

As someone who has spent years working with technology and helping others solve problems, I wanted to create a tool that makes online safety easier and more accessible. Instead of expecting users to understand complex security indicators, Fraudly brings together multiple trust signals—such as reputation data, security indicators, reviews, domain information, and scam intelligence—and presents them in a simple, easy-to-understand format.

The mission behind Fraudly is straightforward: help people make safer decisions online before they click, buy, or share personal information.

What started as a simple website checker has grown into a broader vision of improving online scam awareness through trust scoring, scam education, security insights, and tools that help both individuals and businesses stay safer online.

See it. Check it. Trust it.

Diffyn's answer:

I started working on Diffyn when I notice that prompting has become an essential part of work across many industries. While there are version control platofrms like github, they are not designed for just prompt management are can be overkill such applications, it is also not integrated natively with various LLMs and relevant tools for users to validate ideas and visualise results properly.

Fraudly.app's answer

Fraudly is currently focused on individual consumers and early adopters who use the platform to verify websites, online stores, and suspicious links before interacting with them.

We are also expanding into small business scam-awareness and employee education solutions, helping organizations improve their awareness of phishing, online fraud, and social engineering risks.

As an early-stage product, our focus is on building a trusted platform, listening to user feedback, and continuously improving the service rather than serving large enterprise customers.