{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T04:57:26Z","timestamp":1783573046052,"version":"3.55.0"},"reference-count":31,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:00:00Z","timestamp":1766966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Digital"],"abstract":"<jats:p>Decentralized Autonomous Organizations (DAOs) suffer from critical governance challenges, such as low voter participation, large token holders\u2019 dominance, and inefficient proposal analysis by manual processes. We propose APOLLO (Autonomous Predictive On-Chain Learning Orchestrator), an AI-powered approach that automates the governance lifecycle in order to address these problems. The gemma-3-4b Large Language Model (LLM) in conjunction with Retrieval-Augmented Generation (RAG) powers APOLLO\u2019s multi-agent system, which enhances contextual comprehension of proposals. The system enhances governance by merging real-time on-chain and off-chain data, ensuring adaptive decision-making. Automated proposal writing, logistic regression-based approval probability prediction, and real-time vote outcome analysis with contextual feature-based confidence scores are some of the major advancements. LLM is used to draft proposals and a feedback loop to enrich its knowledge base, reducing whale dominance and voter apathy with a transparent, bias-resistant system. This work demonstrates the revolutionary potential of AI in promoting decentralized governance, paving the way for more effective, inclusive, and dynamic DAO systems.<\/jats:p>","DOI":"10.3390\/digital6010003","type":"journal-article","created":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T15:05:01Z","timestamp":1767193501000},"page":"3","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["APOLLO: Autonomous Predictive On-Chain Learning Orchestrator for AI-Driven Blockchain Governance"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3112-6568","authenticated-orcid":false,"given":"Istiaque","family":"Ahmed","sequence":"first","affiliation":[{"name":"Graduate School of Informatics, Osaka Metropolitan University, Osaka 558-8585, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3251-3385","authenticated-orcid":false,"given":"Zubaer Mahmood","family":"Zubraj","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunication Engineering, East Delta University, Chattogram 4203, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8361-4870","authenticated-orcid":false,"given":"Md Sadek","family":"Ferdous","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, BRAC University, Dhaka 1212, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3354-8964","authenticated-orcid":false,"given":"Tadashi","family":"Nakano","sequence":"additional","affiliation":[{"name":"Graduate School of Informatics, Osaka Metropolitan University, Osaka 558-8585, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2744-0079","authenticated-orcid":false,"given":"Thi Hong","family":"Tran","sequence":"additional","affiliation":[{"name":"Graduate School of Informatics, Osaka Metropolitan University, Osaka 558-8585, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102734","DOI":"10.1016\/j.jcorpfin.2025.102734","article-title":"A review of DAO governance: Recent literature and emerging trends","volume":"91","author":"Han","year":"2025","journal-title":"J. Corp. Financ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"100208","DOI":"10.1016\/j.bcra.2024.100208","article-title":"Analyzing Voting Power in Decentralized Governance: Who Controls DAOs?","volume":"5","author":"Fritsch","year":"2024","journal-title":"Blockchain Res. Appl."},{"key":"ref_3","unstructured":"(2025, October 01). Tally Documentation. Available online: https:\/\/docs.tally.xyz\/."},{"key":"ref_4","first-page":"397","article-title":"Governance challenges of blockchain and decentralized autonomous organizations","volume":"24","author":"Rikken","year":"2019","journal-title":"Inf. Polity"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Cronin, I. (2024). Autonomous AI Agents: Decision-Making, Data, and Algorithms. Understanding Generative AI Business Applications: A Guide to Technical Principles and Real-World Applications, Apress.","DOI":"10.1007\/979-8-8688-0282-9"},{"key":"ref_6","unstructured":"Luo, Y., Feng, Y., Xu, J., Tasca, P., and Liu, Y. (2025). LLM-Powered Multi-Agent System for Automated Crypto Portfolio Management. arXiv."},{"key":"ref_7","unstructured":"Ziegler, C., Miranda, M., Cao, G., Arentoft, G., and Nam, D.W. (2024). Classifying Proposals of Decentralized Autonomous Organizations Using Large Language Models. arXiv."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Song, Z., Yan, B., Liu, Y., Fang, M., Li, M., Yan, R., and Chen, X. (2025). Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey. arXiv.","DOI":"10.18653\/v1\/2025.findings-emnlp.1379"},{"key":"ref_9","unstructured":"(2025, October 01). Uniswap Governance. Available online: https:\/\/www.uniswapfoundation.org\/governance."},{"key":"ref_10","unstructured":"(2025, October 01). Ethereum Governance. Available online: https:\/\/ethereum.org\/governance."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1257\/pandp.20181002","article-title":"Quadratic Voting: How Mechanism Design Can Radicalize Democracy","volume":"108","author":"Lalley","year":"2018","journal-title":"AEA Pap. Proc."},{"key":"ref_12","first-page":"9459","article-title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","volume":"Volume 33","author":"Larochelle","year":"2020","journal-title":"Proceedings of the Advances in Neural Information Processing Systems, NeurIPS 2020, Virtual, 6\u201312 December 2020"},{"key":"ref_13","unstructured":"Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E.H., Le, Q.V., and Zhou, D. (December, January 28). Chain-of-thought prompting elicits reasoning in large language models. Proceedings of the NIPS\u201922: 36th International Conference on Neural Information Processing Systems, New Orleans, LA, USA. Available online: https:\/\/dl.acm.org\/doi\/10.5555\/3600270.3602070."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Srinivasan, D., and Jain, L.C. (2010). An Introduction to Multi-Agent Systems. Innovations in Multi-Agent Systems and Applications\u20141, Springer.","DOI":"10.1007\/978-3-642-14435-6"},{"key":"ref_15","unstructured":"(2025, October 01). LangChain: Multi-Agent Systems. Available online: https:\/\/docs.langchain.com\/oss\/python\/langchain\/multi-agent."},{"key":"ref_16","unstructured":"(2025, October 01). Ganache Truffle Suite. Available online: https:\/\/archive.trufflesuite.com\/ganache\/."},{"key":"ref_17","unstructured":"Phillips, D. (2025, October 01). What Is Vote Escrow?. Available online: https:\/\/coinmarketcap.com\/academy\/article\/what-is-vote-escrow."},{"key":"ref_18","unstructured":"Zoltu, M. (2025, October 01). EIP-2718: Typed Transaction Envelope. Available online: https:\/\/eips.ethereum.org\/EIPS\/eip-2718."},{"key":"ref_19","unstructured":"(2025, October 01). The Vector Database for Scale in Production. Available online: https:\/\/www.pinecone.io\/."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Hung, A.H.C. (2025). DAO as Rhizome: Reimagining Rules, Governance and Organisations. Law Crit.","DOI":"10.1007\/s10978-025-09432-w"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s41109-020-00342-7","article-title":"Forecasting elections results via the voter model with stubborn nodes","volume":"6","author":"Vendeville","year":"2021","journal-title":"Appl. Netw. Sci."},{"key":"ref_22","unstructured":"Moustafa, M. (2025, October 01). Generating Proposals for DAOs Using LLM: An Experiment. Available online: https:\/\/www.linumlabs.com\/articles\/generating-proposals-for-daos-using-llm-an-experiment."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1761","DOI":"10.38124\/ijisrt\/25apr1147","article-title":"Fin-RAG: A RAG System for Financial Documents","volume":"10","author":"Kannammal","year":"2025","journal-title":"Int. J. Innov. Sci. Res. Technol."},{"key":"ref_24","unstructured":"David, I., Zhou, L., Song, D., Gervais, A., and Qin, K. (2025). Decompiling Smart Contracts with a Large Language Model. arXiv."},{"key":"ref_25","unstructured":"Databricks, A. (2025, October 01). RAG Application Governance and LLMOps. Available online: https:\/\/learn.microsoft.com\/en-us\/azure\/databricks\/generative-ai\/tutorials\/ai-cookbook\/fundamentals-governance-llmops."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2814","DOI":"10.1109\/TCSS.2025.3539889","article-title":"Understanding DAOs: An Empirical Study on Governance Dynamics","volume":"12","author":"Wang","year":"2025","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1108\/RAUSP-08-2023-0162","article-title":"Exploring off-chain voting and blockchain in decentralized autonomous organizations","volume":"59","author":"Monteiro","year":"2024","journal-title":"RAUSP Manag. J."},{"key":"ref_28","unstructured":"Ahmed, I., and Zubraj, Z.M. (2025, October 01). Autonomous-Predictive-On-Chain-Learning-Orchestrator (APOLLO) for AI-Driven Blockchain Governance. Available online: https:\/\/github.com\/istiaque010\/Autonomous-Predictive-On-Chain-Learning-Orchestrator-APOLLO-for-AI-Driven-Blockchain-Governance.git."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Cormack, G.V., Clarke, C.L.A., and Buettcher, S. (2009, January 19\u201323). Reciprocal rank fusion outperforms condorcet and individual rank learning methods. Proceedings of the SIGIR \u201909: 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Boston, MA, USA.","DOI":"10.1145\/1571941.1572114"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/TPAMI.2018.2889473","article-title":"Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs","volume":"42","author":"Malkov","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1109\/TBDATA.2019.2921572","article-title":"Billion-Scale Similarity Search with GPUs","volume":"7","author":"Johnson","year":"2021","journal-title":"IEEE Trans. Big Data"}],"container-title":["Digital"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2673-6470\/6\/1\/3\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T15:33:28Z","timestamp":1767195208000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2673-6470\/6\/1\/3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,29]]},"references-count":31,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,3]]}},"alternative-id":["digital6010003"],"URL":"https:\/\/doi.org\/10.3390\/digital6010003","relation":{},"ISSN":["2673-6470"],"issn-type":[{"value":"2673-6470","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,29]]}}}