CoinQuant has upgraded its no-code trading platform into a unified “trading intelligence” architecture that serves both human traders and fully autonomous AI agents — a move that could accelerate machine-to-machine activity across crypto markets.
Since launch, CoinQuant says its platform has attracted more than 15,000 users with a simple promise: translate plain-English strategy descriptions into complete algorithmic trading systems. That includes entries and exits, position sizing, filters and risk rules — all generated from verbal or written input and backtested at tick-level without any coding. “I spoke one idea into CoinQuant, ran the test, and launched a bot on my lunch break,” said Alex K., a software engineer using the platform.
The key expansion is agent-native infrastructure: autonomous AI agents can now deploy, test and execute crypto trading strategies end-to-end without human oversight at each step. That places CoinQuant squarely in the fast-growing machine-to-machine crypto infrastructure market. Research firm Keyrock estimates AI agents settled more than $73 million across 176 million blockchain transactions in the 12 months through April 2026, and the broader opportunity spans over a million potential autonomous trading agents active across crypto markets.
This launch comes amid a broader industry push to make agents first-class economic participants in crypto. Examples include Coinbase’s roll-out of agentic wallets via its x402 protocol in February 2026 (processing more than 50 million transactions), Circle’s May 2026 Agent Stack (wallets, an agent marketplace and nanopayments for sub-cent AI commerce), and MoonPay’s MoonAgents efforts to let agents spend stablecoins at point-of-sale.
Where those projects focus on payments, wallets and rails, CoinQuant targets the strategy layer — the intelligence engine that lets agents build and execute trading approaches without being pre-programmed. By combining no-code strategy creation with agentic execution, CoinQuant is positioning itself to make it far easier to scale autonomous trading strategies across the growing ecosystem of AI-native crypto infrastructure.
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