Alternatives
Products that do what HyperVibe does
Tap up or down. Real perps on HyperLiquid, one tap.
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Hey HN, I just released Tradofire, a crypto trading app I built using a lot of cursor chatgpt and claude for over a year. The main idea of the app is very simple - to swipe on pre-prepared trading setups (like tinder) and if you right swipe it opens a position. The execution of this simple idea was much more complex and tbh I could not have done it without AI. Here's a quick rundown of the main features: Swipe-to-Trade UI: Quickly initiate long or short positions with intuitive swipe gestures. Real-Time Trade Signals: Get curated crypto signals from the market delivered proactively, helping…
2025 · apps.apple.com
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2021 · tuned.com
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You bet on the direction of crypto chart in the next 60 secs (up/down). If you're right, you can win >60%, if you're wrong, you lose your investment. Onboard just with an ETH transfer, no KYC. Fun mode available.
2022 · popcoin.gg
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Real-time whale tracking & analytics for Hyperliquid traders
Jul 2026 · hyperinteldata.com
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Describe, backtest, and automate your trading strategy
5d ago · hey-traders.com
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Hi HN, I'm a solo dev and for the last few months I've been building Hikaro, a tool to find statistically significant trading signals for [e.g., US equities, crypto, forex]. I built this to solve my own problem: I was tired of backtests that looked great on paper but failed in practice. Simple metrics like "win rate" can be misleading, so I wanted a way to quickly tell if a signal's performance was genuine or just noise. Hikaro ingests daily market data and runs statistical analysis on various trading signals. The goal is to surface signals with strong properties, like: Low p-value: Evidence…
Sep 2025 · hikaro.app
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Post-Opus 4.6, LLMs feel much better at using bash, code, local files, and tools. So I kept coming back to a simple question: if a model can use a computer reasonably well, why can’t I just give it my broker account, a strategy, and let it trade? My conclusion is that the blocker is not model capability in the abstract. It is the system around the model. A raw LLM breaks on a few practical things almost immediately: • no persistent operating memory across sessions • no trustworthy record of what it did and why • no hard approval boundary before money moves • no cheap always-on monitoring if…
Mar 2026 · github.com
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