AegisYield
Maximize DeFi Yield, Minimize the Work
About
The problem it solves --- ## 🧩 Problem AegisYield Solves In the current DeFi landscape, lending yields vary drastically across protocols, and those APYs fluctuate frequently based on supply/demand dynamics. Users who want to maximize their yield face several challenges: ### ❗ Key Problems in Existing DeFi Lending: * **Manual Protocol Monitoring**: Users must constantly check rates across platforms like Aave, Morpho, Compound, etc. APYs change frequently—missing a better yield can mean losing long-term profit. * **No Automation**: There's no native way to auto-migrate assets to the protocol with the highest APY. Users must manually withdraw and re-deposit, incurring gas and slippage costs. * **Fragmented Yield Data**: APY data is off-chain and inconsistent across platforms. This makes it difficult for smart contracts to access real-world yield rates for informed decisions. * **High Barrier for Non-Experts**: New DeFi users don’t know how to evaluate protocols or yields. They often stick to one platform and miss out on better opportunities. * **Centralized Yield Optimizers Are Risky**: Some yield optimizers are custodial or rely on multisig governance. They lack transparency and can introduce centralization risk. --- ## ✅ How AegisYield Solves It * **🔗 Uses Chainlink Functions** to fetch off-chain APY data (from DefiLlama) and bring it on-chain securely. * **⏱ Uses Chainlink Automation** to trigger daily strategy updates and rebalance user funds. * **🔁 Auto-allocates assets** to the best-yielding protocol—no manual input required. * **🧱 Modular protocol adapter system** allows easy expansion to more protocols. * **🛡️ Non-custodial and on-chain**—users retain full control of their assets at all times.
How it's made
Challenges we ran into ## Challenges ## 🧠 Standardizing Protocol Interfaces **Problem**: Different lending protocols like Aave, Sparklend, and Compound have unique interfaces, functions, and even their own yield calculation models. This makes it a hassle to interact with multiple protocols. **Solution**: We tackled this by building a modular adapter pattern. we created and used multiple protocol interfaces for multiple protocols. --- ## 🔗 Fetching Off-Chain APY Data On-Chain (Chainlink Functions) **Problem**: To make smart, informed decisions, our system needed access to real-world lending APY data from sources like DefiLlama. The catch? Ethereum smart contracts can't natively make HTTP requests to fetch this off-chain information. **Solution**: Our answer was to integrate Chainlink Functions. This powerful tool allowed our smart contract to securely and reliably fetch the necessary APY data directly from DefiLlama’s public API, bridging the gap between off-chain data and on-chain logic. --- ## ⏱️ Time-Based Automation Without Central Control **Problem**: We needed a way to automatically update and rebalance our lending strategies on a set schedule, specifically every 24 hours. The challenge was doing this without relying on a centralized script or a manual trigger, which introduces points of failure and goes against the decentralized ethos. **Solution**: We solved this by integrating Chainlink Automation. This enabled us to schedule on-chain calls that execute automatically, ensuring our strategies are updated and rebalanced precisely when needed, all in a decentralized manner.