Atua AI (TUA) Releases Multi-Node Cognitive Engine for Autonomous Web3 Task Execution

Singapore, Singapore Nov 23, 2025 (Issuewire.com) - Atua AI (TUA), the decentralized AI automation and productivity platform, has released a Multi-Node Cognitive Engine designed to power autonomous task execution across Web3 ecosystems. This breakthrough engine introduces distributed intelligence that allows AI-driven workflows to operate independently, coordinate tasks across nodes, and maintain consistent performance under complex multichain conditions.
The Multi-Node Cognitive Engine leverages advanced reasoning, dynamic workload routing, and decentralized decision-making logic to enable self-managing task execution across blockchain networks such as Ethereum, BNB Chain, and XRP Ledger. When combined with Atua AIs modular tools including Chat, Writer, and Coder the engine delivers stronger throughput, improved adaptability, and reliable multi-step automation without manual oversight.
Autonomous execution is the future of decentralized automation, said J. King Kasr, Chief Scientist at KaJ Labs. Our Multi-Node Cognitive Engine brings intelligence, independence, and scale to Web3 workflows, empowering developers to build systems that operate seamlessly with minimal intervention.
This release reinforces Atua AIs mission to deliver intelligent, modular infrastructure for next-generation decentralized applications. By enabling parallel, autonomous task handling, the Multi-Node Cognitive Engine provides enterprises with a powerful foundation for scaling AI-driven operations across complex Web3 environments.
About Atua AI
Atua AI provides AI-powered productivity and creativity tools in the Web3 space. Its features include Chat, Writer, Coder, Imagine, Transcriber, Voiceover, Voice Isolator, and Classifier. By combining decentralized infrastructure with modular AI intelligence, Atua AI empowers enterprises, developers, and creators to build scalable workflows and reliable automation across blockchain networks.
Media Contact
KaJ Labs
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Source :KaJ Labs
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