TradeRead
AI-powered chart analysis in seconds
What it does
TradeRead turns any trading chart into a full AI analysis in seconds. Upload a screenshot or pick a symbol directly from the built-in TradingView widget — and get entry price, stop loss, take profit levels, risk/reward ratio, and directional bias. Works with any platform: TradingView, Binance, MetaTrader, and more. No signup required for your first 5 analyses. Built for traders who want a quick second opinion before entering a trade.
Does the same job
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TradeIQ - AI Trading Assistant AppJun 2026 · apps.apple.com · ▲3Snap any Trading chart. Get instant AI technical analysis.
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Hi HN, About a year ago I started tinkering with drawing candlestick charts on an HTML canvas. What began as a small experiment turned into a full-blown crypto charting library. At some point I asked myself: could this actually become a competitor to TradingView? That felt overwhelming, since TradingView has an enormous feature set. Still, I kept building — partly because I enjoy side projects more than watching TV By the summer, I had a working SaaS version. But it felt like it was missing something that would make it truly stand out. Then I realized: the chart itself should be AI-powered.…
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Parallel agents, diff reviewer, and multi-model comparisons
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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Dev tools · May 2026 · github.com