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Zircuit Launches “Hyperliquid for AI Trading,” an AI-Powered Cross-Chain Trading Engine

Desi Rossilawati
Jumat, 25 Juli 2025 | 20:39 WIB
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Zircuit Launches “Hyperliquid for AI Trading,” an AI-Powered Cross-Chain Trading Engine
VISI.NEWS | BANDUNG - Zircuit, a Layer-2 blockchain built on AI and known for its robust security, has announced the launch of an AI-powered bot trading engine called "Hyperliquid for AI Trading." The engine provides real-time signal detection and auto-routing capabilities across chains on both the Ethereum Virtual Machine (EVM) network and Solana. The closed beta phase of this trading engine is set to begin at the end of July 2025, with a public launch scheduled for August 2025.

Revolutionizing AI Trading Across Chains

"Hyperliquid for AI Trading" is designed to revolutionize automated trading by supporting cross-chain capabilities, enabling users to utilize liquidity from both EVM and Solana ecosystems. This innovation aims to enhance efficiency and accessibility in the decentralized trading landscape. Following the beta testing period, Zircuit also plans to launch an ecosystem incentive program in Q4 2025, which is expected to significantly boost platform adoption.

$950M TVL and Advanced AI Security

Currently, Zircuit holds over $950 million in Total Value Locked (TVL), reflecting a high level of trust from the crypto community. The platform leverages cutting-edge AI-based security technologies, including its proprietary Sequencer-Level Security (SLS) system, which is designed to safeguard transactions for users and developers.

Q4 Incentive Program: Fueling Ecosystem Growth

Zircuit’s Q4 incentive program promises the distribution of 10 million $ZRC tokens, which is expected to attract developers to integrate new AI models using the soon-to-be-released Software Development Kit (SDK). With the adoption of its secure vault architecture and growing community enthusiasm, Zircuit is poised to become a central hub for innovation in the fields of AI and DeFi. Not financial advice do you own research @gvr

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