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Hypernova is an on-chain proprietary trading protocol built on Hyperliquid. It codifies evaluation, funding, risk management, and payouts into smart contracts. Traders who pass the assessment can receive up to $200,000 in initial capital, trade perpetual futures with a 90% profit share, and withdraw eligible USDC profits instantly via smart contracts. The platform features a hybrid hedging model that dynamically adjusts exposure based on trader behavior, alongside proprietary trading terminal, analytics tools, and API/SDK.
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About Hypernova
Hypernova is an on-chain proprietary trading protocol built on Hyperliquid. Its core business is to provide trader-funded accounts (up to $200,000) after an evaluation, with profit sharing. Instead of relying on manual policies, capital allocation, performance tracking, and payout settlement are written into smart contracts and executed on-chain.
Its narrative focuses on "trustless prop trading." Traditional prop firms often use opaque B-book arrangements, where consistently profitable traders become liabilities, and payouts are slow or rules are arbitrary. Hypernova dynamically assigns A/B books based on trader quality: high-quality traders are routed to real markets and the platform takes losses; all risk parameters and payment records are publicly verifiable, reducing conflicts of interest and disputes.
In recent development, its closed alpha launched on May 1, 2026, attracted 250 traders, funded 20+ traders, paid out over $30,000 in profits, and planned a public launch within two months. However, by August 2026, an airdrop tracker downgraded its status from "confirmed" to "potential clue," with no verification or claim stage, indicating reward arrangements remain uncertain.
Hypernova was founded in September 2025 and began fundraising simultaneously. In mid-October 2025, it closed a $3 million pre-seed round led by Lemniscap, oversubscribed by 3x, with $1 million allocated to a trader payout reserve. On May 1, 2026, it launched a closed alpha. By late May, it had onboarded 250 traders, funded over 20 accounts, and paid out more than $30,000 in profits, validating its onchain smart-contract instant settlement and payout system on Hyperliquid. Its core design dynamically routes traders between A-book and B-book models based on trader quality, aiming to address the traditional prop-firm problems of opaque payouts and restrictions on profitable traders. The platform expects to launch publicly within two months. These milestones mark its progression from funding to product validation, with long-term significance for the onchain prop-trading sector.
Hypernova, an on-chain prop trading protocol on Hyperliquid, raised a $3M oversubscribed pre-seed round led by Lemniscap (closed Oct, announced later), with participation from Very Early Ventures, CMS Holdings, and Hyperliquid ecosystem angels. The round was allocated $1M to a public on-chain payout reserve.
Since its closed alpha on May 1, 2026, Hypernova onboarded 250 traders, funded 20+ accounts, and processed $30K+ in payouts. By August, it moved to private beta, surpassing 3,300 sign-ups, $2B in trading volume, and $555K+ in trader payouts. Average payout settlement time is 6.1 seconds.
Future roadmap: Hypernova plans a public launch within two months, scale capital behind consistently profitable traders, route their trading to real markets (A-book), and expand revenue lines beyond one-time assessment fees. The long-term vision is a distributed, meritocratic trading desk where on-chain performance records determine real capital allocation.
Co-founder & CEO Anar Bayramov: former venture investor at RockawayX (led DeFi investments, early investor in Breakout, later acquired by Kraken), DeFi strategist at Pluto Digital, systematic trader at a crypto trading firm; MSc in Financial Technology from Imperial College London.
Co-founder & CTO Nijat Bakhshaliyev: former Senior Software Engineer at Coinbase (institutional custody & Onchain Wallet), AVP at Citi (commodities e-trading), Java developer (G10 rates pricing/electronic trading); previously J.P. Morgan and Thales; MSc in Computing Science from Imperial College London.