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18 projects
用AI矢量追踪将设计提取转换为可编辑的SVG文件。
u/Strong-Thing-8888 · Reddit
I built an AI tool that turns complex artwork into clean, editable SVG files I created DesaynClaw for designers who spend too much time manually tracing logos, jersey graphics, and detailed artwork. Upload a PNG or JPG, let the tool extract and clean the design, then export it as an editable SVG. It also includes background removal, image upscaling, palette tools, and before-and-after comparison. The platform is still improving, so I’m looking for designers who can test it
每周自动追踪竞争对手的定价、功能和消息变化。
@Caden1Fenn · X
Intel Brief — tracks what your competitors change (pricing, features, positioning) and delivers it to your inbox weekly. Built for indie SaaS founders.
用 AI 检测监控竞争对手的定价、定位和信息变化。
mhhabib · Product Hunt
IntelDif AI-driven competitive intelligence without the alert fatigue
使用 FRAI 扫描网站中的 AI 使用情况，并测试聊天机器人的偏差和安全性。
@sebuzdugan · X
building @getfrai , an open source toolkit that helps ML engineers navigate EU AI Act compliance, model cards, risk files, the boring but necessary stuff
一款 AI agent 浏览器扩展，可以执行任务、提供带引用的研究结果，并在你工作时记住信息。
@kurvantHQ · X
通过AI聊天界面查询公司文档和内部指南。
@DD_Ferel · X
We built IntelliBase AI: a smart knowledge base that "learns" directly from your company's own documents, so HR & Ops teams can ask questions naturally instead of digging through files one by one. 🌐 Interested in trying it for your team? Comment or DM us
Valta is the financial infrastructure layer for autonomous AI agents. Give every agent its own wallet, spending limits, approval flows, and audit trail.
@DeboJolaosho · X
Building Valta- financial controls for AI every agent its own wallet, spending limits, audit trail, and kill switch. Still in free beta.
AI 应用安全扫描器，检测泄露的密钥和配置问题。
thfothijn · Product Hunt
OpzyAI Finds what your AI-built app leaks — your editor fixes it
支持GPT、Claude、Gemini和Grok的聊天应用，用于学习和编程。
@DovyRuo · X
由AI驱动的代码审查工具，在microVM中运行代码来捕获更多错误。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db
