The Definitive Due Diligence Platform for Hyperliquid Vaults

🧠 Project Name

VaultSight

🔍 Description

VaultSight is an institutional-grade analytics platform designed to solve the due diligence dilemma for investors in Hyperliquid's on-chain copy-trading ecosystem. While Hyperliquid offers a powerful, permissionless marketplace of trading strategies, its native interface provides only surface-level data, making it difficult for depositors to properly vet vault leaders. VaultSight transforms raw, on-chain data into actionable intelligence, empowering users with a comprehensive suite of performance and risk metrics to make smarter, data-driven investment decisions.

🛠️ How It Works

The core of VaultSight is a web application that provides a 360-degree view of any Hyperliquid vault's performance and strategy. Users begin at our dynamic leaderboard, which allows them to discover, filter, and sort all public vaults by critical metrics like TVL, vault age, and risk-adjusted return (Sharpe Ratio)—a significant upgrade over the native interface.

Clicking any vault leads to a dedicated Analytics Dashboard, the heart of our premium offering. Here, users can visualize a vault's historical performance on an interactive equity curve and compare it against benchmarks like Bitcoin. The dashboard features an insti

tutional-grade risk metrics suite, calculating essential indicators that professional fund managers rely on, including:

• Maximum Drawdown (MDD): To show the largest historical loss.

• Sharpe & Sortino Ratios: To measure risk-adjusted performance.

• Annualized Volatility: To quantify return fluctuations.

Finally, our "Strategy DNA Analysis" deconstructs a leader's entire trading history to reveal their habits, such as average leverage, holding period, win rate, and asset concentration. For a personalized experience, the "My Portfolio" dashboard allows users to get a consolidated performance view of their own vault investments.

Technical Highlights:

• Frontend: Built with Next.js (React) and Tailwind CSS, creating a fast, responsive, and modern user interface. The front end is fully self-contained for this demo, using mock data to simulate the full user experience without external dependencies.

• Backend Design (Proposed): The proposed backend is a Python/FastAPI engine designed to ingest data from Allium's indexed Hyperliquid database, perform complex calculations using Pandas/NumPy, and store results in a PostgreSQL database with a Redis cache for performance.

💻 Demo

Video Demo: https://www.loom.com/share/53fd7ea31e9246ac870465f6dbb29890?sid=3fde10e9-f233-4df9-96dd-360bb359a2bb

📂 Project Links

• Paper: https://docs.google.com/document/d/1F9W0yzMc2lGU74c_nAL206R6dM9MFky5h2FHZN0T_Xc/edit?usp=sharing

• Code: https://github.com/vaultsight/vs

• Presentation: https://www.vaultsight.xyz/

• Live Demo: http://206.189.92.214:8080/

👥 Team

Fodé Diop (https://x.com/diopfode)