AI-based omnichain yield optimization and integrated liquidity lending protocol @NetworkNoya , @superformxyz , @0xSoulProtocol As the decentralized finance environment expands across multiple blockchain networks, yield opportunities and liquidity have become dispersed, resulting in a complex situation where users must directly understand and manage the bridge structures, gas costs, and individual protocol risk factors of each chain. To address these structural issues, an architecture has emerged that combines AI-based decision-making systems, an omnichain execution layer, and integrated liquidity lending infrastructure into a single stack. This structure is designed to allow assets to be efficiently managed across multiple chains and protocols without direct user intervention by separating yet organically connecting different functions such as capital allocation, execution, settlement, and collateral management. The starting point of this stack is the AI-based yield decision-making system, NOYA ai. NOYA ai analyzes on-chain data generated across multiple blockchains, along with factors such as yield, liquidity depth, bridge fees, and gas costs, to calculate where it is most rational to allocate capital. In this process, the predictive model operates internally, and during the execution phase, it is designed to perform asset movements or reallocations only within an approved range. Execution is carried out by a keeper with a multi-signature structure, and a node acting as a monitor continuously oversees this, allowing for intervention in case of abnormal behavior. This system demonstrates that AI can lead to actual capital allocation rather than merely presenting signals, while also incorporating control mechanisms through verification and monitoring procedures. Once NOYA ai makes a decision, that decision is implemented as actual transactions through the omnichain execution layer, Superform. Superform provides a structure that bundles tasks that users need to perform across multiple chains into a single intent-based command. This allows users to execute deposits, transfers, and yield strategies across multiple chains with just a single signature. Internally, it is designed using a hook-based architecture and bundling mechanism to ensure that even if some tasks fail, the entire process is not invalidated, and messages between chains utilize various interoperable messaging protocols to select the optimal path in terms of cost and security. Additionally, Superform manages actual assets on the original chain while integrating yield flows and status information through a tokenized position representation of exposure to specific vaults. In a situation where assets are distributed across multiple chains, the liquidity lending infrastructure from Soul Labs is used to manage collateral and loans integratively. Soul Labs provides a structure that allows users to borrow on one chain based on collateral deposited on another chain without physically moving the assets. The key element enabling this is a risk assessment system that acts as a central controller, calculating the positions of all connected chains into a single global health indicator. When a user deposits assets on a specific chain, those assets are recorded in the form of tokens that generate interest, and this information is synchronized with other chains to reflect the overall borrowing limit. In this process, the interest rate structure is not identical to the underlying protocol, and an adjusted model is applied in high utilization ranges to prevent liquidity depletion. As these three components combine, risk management is also conducted from an omnichain perspective rather than a single chain unit. Price information is cross-verified through multiple oracle sources, and if the global health indicator falls below a certain threshold due to a decline in collateral value, liquidation can occur on any chain. During the liquidation process, collateral distributed across multiple chains is proportionally reclaimed, and predetermined penalties and rules for handling the remaining amounts are applied. At the same time, separate safety mechanisms are placed at each layer to consider factors such as bridge risk, validator failure, and automated decision-making errors. From a user experience perspective, this stack significantly reduces complexity by abstracting multiple chains and protocols into a single interface. Users can understand their status through an integrated position and a single health indicator, without needing to directly handle gas management or the detailed structures of individual chains. However, this simplification comes with the characteristic that the risk calculations and execution procedures operating internally are not directly visible to the user. To complement this, users retain the authority to set limits on automated strategies or recover their assets at any time. As a result, the AI-based omnichain yield optimization and integrated liquidity lending protocol binds the decentralized finance environment into a single continuous capital flow through a structure that separates yet combines the three axes of intelligent capital allocation, omnichain execution, and integrated collateral management. This structure demonstrates a direction that enhances capital efficiency through automated decision-making and execution while maintaining a non-custodial principle that does not directly hold assets. At the same time, it clearly reveals that the importance of system design and verification has become a core element of asset management, as multiple chains are interconnected within a single risk structure. $SO $UP $NOYA