How did you integrate our partners, if any?

VolVantage is built natively for Unichain to solve the "LVR" (Loss Versus Rebalancing) problem for Liquidity Providers. My integration leverages Unichain's Flashblocks through a custom Flashblock-Aware Oracle, allowing the VolVantageHook to monitor pool stress and adjust swap fees with sub-second granularity.

By deploying the full RAD-IH (Risk-Adjusted Dynamic Incentive Hook) suite on the Unichain Sepolia testnet, we’ve created a system where fee escalation and vSTRESS reward minting happen in real-time as the chain processes blocks. This high-speed environment is what makes our "Risk Intelligence" engine effective, as it can react to toxic volatility faster than traditional L1-based hooks. Finally, I've integrated a Showcase Dashboard that connects directly to the Unichain Sepolia RPC to visualize these dynamic adjustments for LPs.

What are the key links to share? (Ex. demo video, GitHub, deck)

Github:https://github.com/Hassene26/VolVantage Slides: https://www.canva.com/design/DAHETW5AG10/adTasjMy4cBFu02ULMDeAQ/edit?utm_content=DAHETW5AG10&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton Project Link:https://vol-vantage.vercel.app/ Demo Video:https://drive.google.com/file/d/1QbXEyi_08bRNJhYBQNf7QOfcLls1ALjf/view?usp=sharing

Problem / Background: What inspired the idea? What problems are you solving?

The problem is that liquidity provision has a timing mismatch problem. When markets are calm, LPs are happy to provide liquidity. When markets are volatile, liquidity disappears. It causes worse slippage, unstable pools. The solution is to incentivize LPs more when providing liquidity is riskier, not when it's easy. What the hook does is i) observe pool conditions ii) compute risk score iii) adjust LP rewards/multipliers accordingly.

Impact: What makes this project unique? What impact will this make?

By integrating a Flashblock-aware Oracle directly into the swap flow, the project dynamically scales LP fees and automates vSTRESS token rewards to protect liquidity providers from toxic volatility in real-time. This project makes a significant impact by directly solving Loss Versus Rebalancing (LVR), converting what was previously arbitrage profit into LP compensation, and stabilizing specialized markets through automated incentives for "brave" liquidity during periods of extreme pool stress.

Challenges: What was challenging about building this project?

Calculating the risk score (thinking about the mathematical side of the formulas), scaling for decimals (i forgot about it, WETH 18 decimals / USDC 6), some issues with libaries compatibility

Team: Who is on the team? What are their backgrounds?