Intent-Driven Decentralization: Architectures for Private, Scalable, and Autonomous Systems
Praveen Kumar Myakala, Anil Kumar Jonnalagadda, Sooraj George Thomas · 2025
This study introduces a novel intent-driven framework designed to advance privacy, scalability, and autonomous coordination in decentralized systems. Unlike traditional transaction-centric models, the proposed architecture allows users to express the desired outcomes through signed intents, enabling flexible and dynamic counterparty discovery without predefined execution paths. Solver-based optimization, leveraging constraint satisfaction techniques, matches, and composes these intents into valid transactions, facilitating complex workflows across heterogeneous trust and consensus environments. Composable privacy is achieved through integrated mechanisms, such as zero-knowledge proofs, homomorphic encryption, and programmable confidentiality, offering fine-grained control over data exposure and state transitions. The framework further supports multi-chain atomic settlement, dynamic rollup instantiation, and cross-domain interoperability, enabling applications across de-centralized finance, supply chain orchestration, and confidential governance. By unifying intent-centric interaction with modular security models, this architecture provides a scalable, privacy-preserving foundation for the next generation of decentralized analytics and autonomous decision-making systems.