
Flate — Crypto AI Terminal
Chat with an AI about crypto markets, wallets, tokens, news, and airdrops with live data charts.
@FlateAI · X
We've just launched!
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60 projects

Chat with an AI about crypto markets, wallets, tokens, news, and airdrops with live data charts.
@FlateAI · X
We've just launched!

AI-powered platform that analyzes Reddit and GitHub discussions to generate customer insights for product decisions.
@Tweet2Tusharr · X
hey everyone 👋 we've been working on something over the last few weeks around customer research. we'd genuinely love if you could spend 5 minutes trying it and tell us what we're getting wrong.

Centralize customer feedback, prioritize with public voting, and share interactive product roadmaps.
@himanshu_b20 · X

@rdbuilds7 https://t.co/UAb8RBPACs
@Munyah_Wacho · X

Paste a contract address to detect Ethereum rug pulls and scams instantly.
@mik3fly__ · X
Here is mine: Check for scam before being scammed!

Web3 platform with a fee-free crypto wallet, games, and gamified economy.
@chaos_mln · X

Compare and benchmark SaaS APIs with independent verified data to make informed build-vs-buy decisions.
fenilsuchak · HN
OpenBenchmarks – Helping agents discover and pick the right SaaS APIs

Create polls, surveys, forms, and live stages with AI verification and reputation-based scoring.
@Eli_Greenfeld · X

Upload a CAS PDF to get AI portfolio analysis with benchmark comparisons and allocation insights.
@iASHeeesh · X

Analyze cryptocurrency markets with Chan Theory patterns, K-line charts, and anomaly detection.
@onehopeA9 · X
用 DAPPOS @dappOS_com 做了一个加密货币缠论分析网站,也是我一直想做没时间做的! 来看看缠论三买的威力: 不是不会写代码。 我自己是程序员,真要硬写当然能写。 但问题是:没时间。🤡 做交易的人都懂,真正消耗人的不是“看一根 K 线”,而是把一堆信息拼起来: K 线结构。 缠论笔、中枢。 一买二买三买。 一卖二卖三卖。 资金费率。 持仓量变化。 成交量异动。 市场舆情。 这些模块涉及太多方面,写得出来,但太费时间。 所以我一直想做一个自己的交易雷达: 接币安历史数据。 用 TradingView 展示 K 线。 自动画缠论结构。 标注买卖点。 再把资金费率、持仓量、成交量和币安广场热度放进去。 想法很清楚。 但一直躺在 TODO 里。 最近用 xbubble 的 Coding 功能试了一下,直接把需求丢进去: “做一个加密货币缠论分析网站,接入币安一年历史数据,用 TradingView 展示 K 线,自动画笔、中枢、一买二买三买、一卖二卖三卖,增加异动分析和币安广场舆情热度。” 它真给我生成了一个能跑的原型。 这次最戳我的不是“AI 会写代码”。 而是 xBubble 把最消耗时间的工程杂活压短了。 以前我自己做: ❌ 搭项目结构 ❌ 爬数据源和图表库 ❌ 写 K 线处理 ❌ 写缠论结构识别 ❌ 做前端交互 ❌ 部署、改样式、修细节 一圈下来,核心想法还没验证,人先累了。 现在变成: ✅ 先描述业务目标 ✅ 让 xBubble 生成可运行原型 ✅ 我再校验规则、调整逻辑、优化体验 ✅ 把时间花在交易理解和产品迭代上 这对程序员其实很有价值。 因为程序员最缺的不是能力,而是时间和注意力。 我这个原型现在大概有几块: 第一,TradingView K 线主图。 用币安数据展示行情,再叠加缠论结构。 第二,笔和中枢。 把原本需要手动盯的结构,先自动画出来。 第三,买卖点雷达。 一买、二买、三买,一卖、二卖、三卖,先帮我筛可能的位置。 第四,异动面板。 资金费率、持仓量、成交量变化,和 K 线结构一起看。 第五,舆情热度。 把币安广场讨论热度也拉进来,看看市场情绪是不是和盘面互相印证。 你可以理解成: 我不是让 AI 替我交易。 我是让 AI 帮我做一个交易前的信息雷达。 我觉得 xBubble 和普通 AI


Launch and trade memecoins on Solana via instant bonding curves.
@coreybricker777 · X
“Graduation Radar” What it does, live and free (no API keys, no wallet connection, zero risk to your funds): •Streams every new token via PumpPortal’s free WebSocket and tracks trades in real time •Scores each token 0–100: curve progress, buy pressure (3 min), unique wallets, age (filters bundled fake pumps), net SOL velocity, minus a penalty if the dev wallet sells •Alerts with sound + optional push notifications when a token crosses your threshold in the graduation runway, plus a separate alert when tokens actually graduate •Built-in paper trading — one-tap hypothetical buys, live P&L, win rate, and average return that persist between sessions How to use it: open the page, let it run 5–10 minutes to populate, hit “Test alert” to check sound, and paper trade the signals for a week or two. If the stats panel shows a real edge after ~100 signals (needs roughly +15% average to clear fees and slippage), then consider tiny real position