US-20260127596-A1 - SYSTEMS AND METHODS FOR AN AI-DRIVEN BLOCKCHAIN PROTOCOL COORDINATING INCENTIVIZED, RISK-AWARE AUTONOMOUS OPERATIONAL AGENTS FOR DYNAMIC RISK/RETURN MANAGEMENT OF TOKENIZED ASSETS

Abstract

A computer-implemented method is provided for autonomously managing tokenized assets associated with an operational venture using a blockchain protocol. The method includes deploying an agent coordination contract on a blockchain network, the contract storing on-chain incentive rules and maintaining lifecycle status and performance metrics for multiple autonomous operational agents. At least one autonomous agent is assigned to the operational venture through the contract. The agent coordination contract receives a performance report from the assigned agent, the report including operational data generated from an executed action. The contract autonomously evaluates the performance report against the on-chain incentive rules to determine a performance outcome. Based on the determined outcome, the agent coordination contract and/or an associated settlement contract autonomously updates one or more of the agent's on-chain lifecycle status, the agent's on-chain performance metrics, and a state of the tokenized assets representing the operational venture.

Inventors

• Balaji Kannaiyan

Assignees

• RMINT Inc

Dates

Publication Date

20260507

Application Date

20260101

Claims (15)

1. 1 . A method for autonomously managing tokenized assets representing an operational venture via a blockchain protocol, the method comprising: a. deploying, by at least one processor, an agent coordination contract on a blockchain network, said agent coordination contract configured to store on-chain incentive rules and manage on-chain lifecycle status and performance metrics for a plurality of autonomous operational agents; b. assigning, via said agent coordination contract, at least one of said plurality of autonomous operational agents to the operational venture; c. receiving, at said agent coordination contract, a performance report from said at least one agent, said report containing operational data resulting from an action performed by said at least one agent; d. autonomously processing, by said agent coordination contract, said performance report against said on-chain incentive rules to determine a performance outcome; and e. autonomously modifying, by said agent coordination contract and/or a settlement contract responsive thereto, at least one of: (i) said at least one agent's on-chain lifecycle status, (ii) said at least one agent's on-chain performance metrics, and (iii) a state of said tokenized assets based on said determined performance outcome.
2. 2 . The method of claim 1 , wherein said performance outcome comprises a reward and/or a penalty, and wherein said autonomously modifying comprises automatically triggering, by said agent coordination contract, a transfer of a protocol-native stablecoin corresponding to said reward and/or penalty.
3. 3 . The method of claim 1 , wherein said on-chain lifecycle status is selected from a plurality of predefined lifecycle statuses comprising at least an ‘Active’ state, a ‘Suspended’ state, and a ‘Terminated’ state.
4. 4 . The method of claim 3 , further comprising preventing said at least one agent from executing a transaction via a custody contract when its on-chain lifecycle status is ‘Suspended’ and/or ‘Terminated’.
5. 5 . The method of claim 1 , further comprising: analyzing, by an AI engine, a history of said on-chain performance metrics to generate a projection of future operational cash flow for the operational venture; and determining a maximum allowable leverage amount for said tokenized assets as a function of said projection of future operational cash flow.
6. 6 . The method of claim 5 , further comprising enabling the issuance of a quantity of protocol-native stablecoins against said tokenized assets as collateral, wherein said quantity is constrained by said determined maximum allowable leverage amount.
7. 7 . The method of claim 5 , wherein said function of said projected future operational cash flow comprises applying a discount factor to said projection to determine a net present value, wherein said maximum allowable leverage amount is based on said net present value.
8. 8 . The method of claim 1 , wherein at least one of said plurality of autonomous operational agents is a specialized Financial Controller Agent (FCA), and wherein the performance report received in step (c) is a cryptographically signed health report from said FCA comprising values for a plurality of on-chain financial performance metrics representing an operational health of the operational venture.
9. 9 . The method of claim 8 , further comprising: determining, by an AI engine based on an analysis of said on-chain financial performance metrics from said health report, an updated set of financial product parameters; and autonomously adjusting, by one or more smart contracts, the terms of at least one financial product related to the operational venture according to said updated parameters.
10. 10 . The method of claim 9 , wherein said at least one financial product is an incentive mechanism for others of said plurality of autonomous operational agents, and said financial product parameters comprise reward and/or penalty amounts stored in said agent coordination contract.
11. 11 . A system for autonomously managing tokenized assets representing an operational venture, the system comprising: a. a blockchain network; b. an agent coordination module deployed on said blockchain network, said module comprising a smart contract configured to: i. store on-chain incentive rules; ii. maintain a registry for a plurality of autonomous operational agents, said registry managing an on-chain lifecycle status and on-chain performance metrics for each of said agents; iii. include a function to receive and autonomously process a performance report from at least one of said agents against said on-chain incentive rules to determine a performance outcome; and iv. include logic to autonomously modify at least one of: said at least one agent's on-chain lifecycle status, said at least one agent's on-chain performance metrics, and/or a state of said tokenized assets based on said determined performance outcome.
12. 12 . The system of claim 11 , wherein said agent coordination module is further configured to trigger a transfer of a protocol-native stablecoin corresponding to a reward and/or penalty as part of processing said performance outcome.
13. 13 . The system of claim 11 , further comprising an AI engine communicatively coupled to said agent coordination module, wherein the AI engine is configured to: retrieve a history of said on-chain performance metrics; generate a projection of future operational cash flow for the operational venture based on an analysis of the history; and determine a maximum allowable leverage amount for said tokenized assets as a function of said projection.
14. 14 . The system of claim 13 , further comprising a stablecoin issuance module configured to enable issuance of a quantity of protocol-native stablecoins against said tokenized assets as collateral, wherein said quantity is constrained by the maximum allowable leverage amount.
15. 15 . The system of claim 11 , wherein at least one of said plurality of autonomous operational agents is a specialized Financial Controller Agent (FCA) configured to generate said performance report as a cryptographically signed health report representing an operational health of the operational venture.

Description

REFERENCE TO RELATED APPLICATIONS This application is a continuation of U.S. patent application Ser. No. 19/201,998, titled “SYSTEMS AND METHODS FOR AN AI-DRIVEN BLOCKCHAIN PROTOCOL COORDINATING INCENTIVIZED, RISK-AWARE AUTONOMOUS OPERATIONAL AGENTS FOR DYNAMIC RISK/RETURN MANAGEMENT OF TOKENIZED ASSETS”, filed May 8, 2025, which in turn is a continuation in part of U.S. patent application Ser. No. 18/116,881, titled “SYSTEMS AND METHODS OF PERSONALIZING SERVICES ASSOCIATED WITH RESTAURANTS FOR PROVIDING A MARKETPLACE FOR FACILITATING TRANSACTIONS”, filed Mar. 3, 2023, each of which is incorporated by reference herein in its entirety. FIELD OF THE INVENTION Embodiments of the present invention relate generally to the field of financial technology, blockchain applications, artificial intelligence (AI) in asset management, and digital asset lifecycle management. More particularly, embodiments relate to AI-driven blockchain protocols specifically designed to coordinate incentivized Risk-Aware Agents (RAAs) for the continuous management of risk and return associated with tokenized assets, wherein said agents autonomously manage operations translating into measurable on-chain financial metrics. BACKGROUND OF THE INVENTION Traditional asset management, particularly for complex ventures or real-world assets, suffers from numerous limitations including manual processes, opacity, latency, and significant intermediary costs. Risk management often relies on periodic human analysis, lacking the continuous adaptability required for volatile markets or dynamic operational environments. Fractional ownership remains cumbersome, hindering liquidity and investor access. Furthermore, specific industries like hospitality (e.g., restaurants) face high entry barriers due to substantial capital requirements for tangible assets (property, equipment), complex deployment processes (site selection, leasing, staffing), and challenging financing environments. Traditional funding routes like bank loans often have stringent requirements, while equity investment may involve loss of control. Existing ownership models (partnerships, LLCs) can lack transparency and efficient mechanisms for profit distribution, especially dynamic adjustments based on real-time performance. While blockchain technology offers potential through tokenization and smart contracts, existing applications remain insufficient for realizing true autonomous asset management focused on continuous risk/return optimization. Many (representing prior art in basic tokenization) provide only static representations of ownership or basic transfer functionalities. They fail to address the core challenges of integrating dynamic valuation, real-world operational management, and achieving genuine asset liquidity beyond simple trading. Crucially, they lack protocols specifically architected to enable, coordinate, and manage a system of autonomous AI agents tasked with this continuous management. Prior art often focuses on using blockchain to automate or make verifiable processes related to time/value of money/assets. They do not address the challenge of a protocol actively managing the operational execution strategy of autonomous agents based on dynamic risk/return goals. Existing approaches combining AI and blockchain typically utilize AI/ML primarily for off-chain analysis, prediction, or triggering predefined on-chain actions. They generally do not disclose protocols featuring specific on-chain incentive structures designed to directly motivate sophisticated Risk-Aware Agent (RAA) actions—including planning, coordination, and execution of operational tasks—based on achieving dynamic risk/return objectives defined by the protocol itself. Mechanisms for protocol-governed, RAA-driven autonomous custody, the integral use of protocol-native stablecoins by RAAs for operational transactions and incentive settlement, verifiable coordination of RAAs for planning and executing tasks impacting asset value, the maintenance of verifiable on-chain RAA performance metrics, and on-chain management of the agent lifecycle are largely absent. Similarly, protocols developed for Decentralized Autonomous Organizations (DAOs) or basic multi-agent system (MAS) coordination on blockchain may automate simple tasks or facilitate agent discovery/communication, but typically focus on governance voting or basic bot execution. They lack the framework for the blockchain protocol itself to actively manage the ongoing operational strategy and execution quality of specialized Risk-Aware Agents (RAAs) using dynamic, performance-based, on-chain financial incentives directly tied to risk and return. The vital feedback loop—whereby the protocol enables RAAs through risk/return incentives, RAAs plan and execute operations, verifiable performance metrics are recorded on-chain, this performance data feeds back influencing AI analysis, and that analysis refines protocol strategy and on-chain RAA incentives controlling how a