Features
Last updated
Last updated
1-Click Liquid Restaking, Liquid Staking
Restake any of our tokens seamlessly with a single transaction. AutoLayer facilitates native restaking across various providers, allowing users to earn Staking Yields, EigenLayer Points, LRT Points, Restaking Rewards, and AutoLayer Points with just a simple click, using any asset. Users will be allowed to mint or trade their assets, and we will route liquidity to the correct provider each time. AutoLayer will even do the swaps on minting to obtain the ETH needed to initiate the staking/restaking proccess.
On AutoLayer, you can explore a diverse selection of various LRTs and LSTs, each with their associated incentives. Once you select any of these assets, you can access a detailed breakdown of all those incentives, the AVSs it validates, their APY over time, and the risk factors associated with the said asset. With just a few clicks, you can easily swap that token to over 100 different assets while preserving all current and future incentives. At any moment, users have the flexibility to swap the LRT/LSTs for any other ERC-20 token.
As more AVSs become operational on EigenLayer, the restaked products will evolve into various financial products, and more competitors will arrive. With AutoLayer, users will be able to update the products in just one click at a very marginal cost.
AutoLayer boasts a robust analytics engine that enables it to calculate all incentives and key performance indicators (KPIs) generated by the user. All tokens reside in the user's wallet, making AutoLayer permissionless and non-custodial. Our engine extracts information from the user's wallet, RPCs, and the blockchain itself, ensuring the most accurate data retrieval. For any restaked token, our engine displays the following information at the very least:
Quantity: This KPI is calculated by how many tokens the user holds.
Profit and Loss (PnL): This KPI is calculated by monitoring the date when the user acquired the tokens and assessing their performance over time.
Staking Rewards: Each LRT has a slightly different staking reward associated with it, and is taken into account when calculating this KPI.
Restaking Annual Percentage Rate (APR): Different reward profiles will be available depending on the validated AVSs and this KPI calculates each one appropriately.
EigenLayer Points: This KPI indicates the accumulated EigenLayer points to date.
LRT Points: Every LRT provider awards points for holding their assets, and this KPI measures all users' earned points.
AutoLayer Rewards: This KPI indicates all trading incentives provided by AutoLayer in addition to existing rewards.
In addition to rewards, AutoLayer also provides a comprehensive assessment of LRT risks. Currently, our focus is on evaluating depeg risks by calculating, in real-time, the amount of LRT used as collateral in decentralized applications such as Aave, Gearbox, Morpho, and Prisma and confront it with the liquidity on DEXs, the contracts that will procced with the liquidation. This data allows us to analyze the potential for liquidation cascades, providing users with critical insights into their exposure to these risks. The larger the collateral relative to the available liquidity, the more susceptible the asset becomes to a significant depeg event.
LSTs and LRTs can be used in DeFi, and issuers can reward those who use them. In AutoLayer, users will be able to easily execute these strategies with just one click and no permissions needed. Users will also be able to evaluate their position over time and swap it for any asset they want by depositing their receipts again (LPs, NFT positions, etc.) on the interface.
AVSs might be the biggest question mark in today's crypto cycle as they will be the driving force behind yields during this time. How well or how poorly they behave will shape the future of the DeFi industry as we know it. This is why auditing AVSs will be important. For every AVS on AutoLayer, we will create a risk score based on two metrics:
Professional Operators TVL: This metric will gauge the involvement of institutional and professional Operators (such as P2P, Ankr, Nethermind, etc.) in an AVS by assessing the amount they have staked on it. This measurement generates a risk profile based on factual data from funds deposited by professionals, rather than subjective opinions.
Community TVL: This metric will quantify the level of support an AVS receives from retail investors, with insight into the amount of retail money backing it. This also contributes to the creation of a risk profile for the AVS.
Sudden changes to these risk scores can help our users stay informed.
