Smart Contract Generation Using AI and Oracle Trust
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Solution Overview
Problem
Current technologies face challenges in easily generating and managing smart contracts in blockchain-based decentralized autonomous organizations (DAOs), particularly in processing real-world contracts due to their analog properties and requiring third-party trust providers for verification.
Innovation Solution
A method and system for generating smart contracts using natural language processing (NLP) and artificial intelligence (AI) to convert contract contents into programmable forms, storing them on a blockchain, and managing trusted data through an Oracle™ system, which provides certification, cryptographic, and trust verification functions, allowing for decentralized trust management without third-party intermediaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If smart contracts are generated manually from real-world contracts, then contract accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The patent replaces manual mechanical processes of contract analysis and smart contract generation with automated AI models and NLP systems. The AI model automatically parses real-world contract text, extracts key terms and conditions, and generates corresponding smart contract code, eliminating the need for manual conversion while maintaining accuracy through intelligent algorithms.
Solution Approach 2:
The patent introduces an intermediary AI model that acts as a bridge between real-world contracts and smart contracts. This intermediary system processes the natural language contract text, interprets legal concepts, and translates them into programmable smart contract logic, thereby automating the conversion process while ensuring accuracy through intelligent mediation.
2Reliability
If third-party trust providers are used for contract verification, then trust reliability is improved, but system complexity and operational overhead increase
Solution Approach 1:
The patent enables the smart contract system to perform self-verification through built-in Oracle mechanisms and automated validation logic. The smart contract automatically verifies the authenticity and integrity of input data using cryptographic proofs and pre-configured verification rules, eliminating the need for external third-party trust providers and reducing system complexity.
Solution Approach 2:
The patent extracts the trust verification function from external third-party providers and integrates it directly into the smart contract system itself. By embedding verification mechanisms within the blockchain protocol and smart contract code, the system removes the dependency on external intermediaries while maintaining trust reliability through decentralized consensus and cryptographic security.
3Ease of operation
If natural language processing is used to convert contracts, then ease of operation is improved, but processing accuracy may deteriorate
Solution Approach 1:
The patent replaces simple NLP text processing with advanced AI models that understand legal semantics and contextual meanings. The AI model goes beyond basic keyword matching to comprehend legal concepts, obligations, and conditions in natural language contracts, thereby maintaining high processing accuracy while enabling easy operation through natural language input.
4Adaptability or versatility
If smart contracts are stored on multiple blockchains, then adaptability is improved, but management complexity increases
Solution Approach 1:
The patent creates a universal smart contract framework that can deploy and execute contracts across multiple blockchain networks through a standardized interface. The system uses a common smart contract template and deployment mechanism that adapts to different blockchain environments, allowing the same contract logic to function universally across various networks without requiring separate management systems for each blockchain.
Data Source
AI summary
Methods of and systems for generating and managing a smart contract may include obtaining contents related to a contract at user request timing in a dialogue environment between users, generating at least one condition associated with the contract, generating a smart contract for the contents related to the contract and the generated condition, and storing the smart contract in a blockchain.