Risk Lens

RiskLens is an AI-powered platform built to help people understand the real risks behind tokenized real-world assets (RWAs). As more real assets—like real estate, commodities, or treasury bonds—move onto the blockchain, investors often struggle to figure out which projects are trustworthy, sustainable, or worth their time. Information is scattered, reporting varies widely, and most tools only scratch the surface. RiskLens was created to solve this problem in a simple, intelligent, and transparent way.

At the heart of RiskLens is a powerful GPT-5–based analysis engine. When a project is submitted, the AI reviews it in depth from multiple perspectives: financial stability, regulation and compliance, the team’s credibility, market fit, tokenomics, yield structure, technical security, and more. This analysis isn’t just guesswork—the platform pulls in real-time data from blockchain oracles and on-chain metrics, giving a grounded, up-to-date view of each asset.

All of this information is distilled into a clear 0–100 risk score, making it easy to compare different RWA projects at a glance. You also get a detailed breakdown of how the score was formed, showing the project’s strengths and weaknesses in each risk category. Nothing is hidden—RiskLens aims to be as transparent as possible so investors understand why a project is considered low or high risk.

But RiskLens doesn’t stop at scoring. It also acts like a personalized investment assistant. Based on your preferences and risk tolerance, the platform suggests opportunities that fit your profile. It keeps monitoring the market and sends alerts if a project’s risk profile changes, if the yield fluctuates, or if something important happens on-chain or off-chain.

On the technical side, RiskLens is built with a modern stack: a smooth and responsive React + TypeScript interface, a secure TypeScript/Express backend, GPT-5 integration, and Mantle Network support for on-chain validation. The interface is designed to feel clean, intuitive, and easy to navigate—even when presenting complex data.