Rocket, a crypto app for “redistribution markets,” has emerged as one of the notable fundraising stories of the past week, securing $1.5 million in a pre-seed round as venture interest continues to build around the next generation of prediction market infrastructure. The raise places Rocket among a group of crypto startups that collectively attracted capital during the final week of December, according to CoinMarketCap.
The funding round was led by Electric Capital, with participation from Tangent, Bodhi Ventures, Amber, Ludlow, Jsquare, and a group of angel investors active across crypto trading and market infrastructure. Rocket is being developed on MegaETH and is incubated by MegaMafia.
Part of a broader funding trend
Rocket’s round came during a week that saw capital flow into a range of crypto startups, from perpetuals and decentralized exchanges to payments and AI platforms. Architect led the period with a $35 million Series A, while neobank Kontigo raised $20 million at the seed stage. Against that, Rocket’s pre-seed raise indicates sustained investor appetite for new market structures tied to on-chain trading and financial primitives.
Unlike several larger rounds focused on scaling established models, Rocket’s funding centers on improving how prediction markets function and how they integrate with real-time crypto trading behavior.
Top Crypto Fundraising Last Week (via @CoinMarketCap on X):
1️⃣ @Architect_Fi – $35.0M; Perpetuals
2️⃣ @kontigo_app – $20.0M; Neobank
3️⃣ @CoinbaxHQ – $4.2M; Payments
4️⃣ @easydotfunx – $2.0M; DEX, Perpetuals
5️⃣ @hodlherai – $1.5M; AI Agents
6️⃣ @userocket_app – $1.5M; Prediction Markets
7️⃣ Nodu – $1.4M; Payments, Developer Tools
From event bets to continuous markets
Rocket describes its product as a shift away from traditional, event-based prediction markets toward what it calls “Redistribution Markets.” Instead of focusing on binary outcomes with fixed settlement dates, Rocket allows users to trade continuously on any live price feed. These can include crypto assets, equities, NFTs, memes, or even odds sourced from existing prediction platforms.
Most prediction markets today, including Polymarket and Kalshi, focus on clearly defined questions with capped outcomes and expiry dates. Users commit capital and wait for resolution, which comes often weeks or months later. Rocket’s model removes fixed expiries and treats prediction as an ongoing pricing process rather than a one-time wager.
Rooted in MegaETH culture, where he’s built one of the strongest mindshares, @nics_off (on X) has joined Rocket “to help tell the story and get the world outside ready for what’s next.”
A key distinction in Rocket’s design is the absence of capped returns. In binary markets, the maximum payoff is typically limited once a position is taken. Rocket instead redistributes value between opposing positions as prices move, meaning gains scale with the degree to which a trader’s conviction diverges from the crowd.
According to the team, this creates a more skill-driven infrastructure that reflects how liquid markets behave, where pricing adjusts continuously, and strong views can compound as momentum builds. The platform positions itself as complementary to existing prediction markets rather than a direct substitute.
Building on existing prediction infrastructure
Rocket’s strategy is to build on top platforms like Polymarket or Kalshi. In this framework, traditional prediction markets become data sources, feeding odds and sentiment into a faster, more fluid trading layer. The result is an abstraction in which prediction markets serve as infrastructure rather than end-user products.
This layered approach aligns with a trend in crypto, where base protocols and applications increasingly serve as composable building blocks for more complex financial systems.
Furthermore, the participation of Electric Capital and other investors suggests growing confidence that prediction markets are entering a new phase of development. Recent commentary from Pantera Capital has also pointed to rising engagement with on-chain prediction data as a signal of shifts in market sentiment and liquidity.
