
Truth.Systems — Verify, or it's a lie.
拖放文件来生成密码学证明它们未被改动——完全在浏览器中验证
@WiseEstSystems · X
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26 projects

拖放文件来生成密码学证明它们未被改动——完全在浏览器中验证
@WiseEstSystems · X

上传肽类COA验证真实性并识别伪造标记。
@DanielGPT2022 · X
I made an app for peptides users, that will hopefully adress their trust issues:

上传简历生成证据型作品集,获得AI评分和改进建议。
@Showcase_app1 · X
Building Showcase: turns a résumé into an editable, evidence-first portfolio for final-year students and new grads. AI-assisted drafts, nothing invented. Build/edit/preview free; live publishing is Pro.

Regra18:通过真实比赛视频判罚和足球规则考试学习足球裁判。
@tiagosoaresv · X

输入公司网址分析 WHOIS、SSL 等信号来生成信任评分。
@CoderJiii · X
🚀 Just launched Veris — a platform that helps verify company legitimacy using WHOIS, SSL, website, contact, social, and legal checks to generate a Trust Score & Risk Level. 🌐 #BuildInPublic #OpenSource #FullStack #React #NodeJS


VeroLente AI用AI技术即时验证新闻、视频、图像和声明,获取真实度分数。
@Banshee_1212 · X
building a deepfake detection platform,

通过 Reddit、HN 和应用商店反馈验证创业想法。
@daicandev · X
Building proven, the tool that gets your product from idea to growing income

在区块链上记录真实成就,通过AI和同行评审验证。
Proof of Awesome — AI 辅助的学术同行评审的共识机制,将你的真实成就永久记录在区块链上,用有意义的人类成就取代传统挖矿 - [更多介绍](https://proof-of-awesome.app/call-for-achievement)

AI驱动的交易策略研究、回测和自动化平台,无需编码。
u/person-person12 · Reddit
The honest reality: Building more SaaS features can do more harm than good Nine months ago, my SaaS was called WealthLearn . At the time we had built Market Research, Backtesting, AI Tools, TradingView Indicators, Portfolio Analysis, Broker Connections, Automation, Education, and even a separate Futures Application for MacOS/Windows. The problem was that every time I explained the company, I had to list all of those things. Our team understood how everything connected b

上传AI对话记录,获取证据支持的报告
@StilThinkng · X
Tired of repeating the same context across ChatGPT, Claude, and Grok? SoulBots builds a privacy-first memory that grows with you across AI. Looking for early testers.

检查论文中的AI写作和抄袭,在提交到Turnitin前自查。
PaperCheck — 论文提交前自查工具,提供 Turnitin 查重 + AI 写作检测报告,帮助学生在正式提交前发现问题