开发者工具5 days ago · 1 次试用
firsteyes AI - Website Audit Tool | Find Why Visitors Don't Convert
firsteyes 网站审计工具，评分转化问题并提供改进建议。
@koustubh018 · X
Hi Kal, I'm building - Find out why first-time visitors leave your website before converting...
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firsteyes 网站审计工具，评分转化问题并提供改进建议。
@koustubh018 · X
Hi Kal, I'm building - Find out why first-time visitors leave your website before converting...
实时仪表板展示 AI-agent 公司的 ARR、MRR、任务和活动。
pro_methe5 · HN
I scrape an $8.5M-ARR company run by AI agents and chart it live
粘贴两个 AI agent 版本，对比治理权限的变化。
stoicstoic · HN
Show HN: Diff two versions of an AI agent and catch silent permission changes
进行免费 SEO 审计，追踪您在 Google 和 AI 搜索引擎中的可见性。
@Sathibuilds
查看你的Vouch Score，衡量ChatGPT、Claude等AI对你的产品的推荐频率。
@abhishek_gadhia · X
Build AI-powered workflows from your notes to automate GTM and sales processes.
@jingconan · X
Hi! Let's Connect! I am building which helps founders to turn ideas to reusable workflows
通过AI简历筛选和结构化面试进行技术候选人招聘。
@__singhritwik · X
监控AI成本，预测支出，为团队设置成本限制。
@eastbase_studio · X
YouEx.ai 是面向 B2B 销售团队的 AI 原生 CRM 平台，自动捕获、丰富、评分和分配线索。
u/youex-ai · Reddit
Built a CRM w/ MCP -- Biggest misunderstanding on first look? We launched an MCP connector a few weeks ago that connects our CRM data. We're still working through our product market fit, so I asked Claude What is the biggest thing people misunderstand about YouEx.ai when they first see it? I was actually not even thinking about researching our actual CRM data, but that's what it did. The answer was actually really insightful: Your own data points at it: a large sha
为你的AI代理添加评估报告，生成可分享的URL展示性能。
adeeonline · HN
AgentsProof – a small project for testing AI agents
AI工具在90秒内通过财务分析和风险评估来压力测试商业创意。
@AIWMCX1 · X
Consultants don’t need more noise. AIWMC Quantis helps turn messy business ideas into clear scenarios, runway views, and risk signals — so you can spend less time rebuilding analysis and more time giving the client a real answer.
使用在微虚拟机中运行代码的AI代码审查来捕获更多漏洞。
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