生产力1 month ago
FeatureSay — AI-Powered Product Feedback Platform
用AI收集用户反馈、优先排序功能需求、发布客户喜爱的功能更新。
@heyayankai · X
💬 Building FeatureSay. A simple platform to collect user feedback, prioritize feature requests, and build what customers actually need.
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用AI收集用户反馈、优先排序功能需求、发布客户喜爱的功能更新。
@heyayankai · X
💬 Building FeatureSay. A simple platform to collect user feedback, prioritize feature requests, and build what customers actually need.
自动对客户反馈提交进行评分、标记和去重。
@ImFabien · X
- feedback management and suggestion box with built-in churn insights for SaaS teams.
从多个平台汇聚反馈，用 AI 分析集中管理。
@GeorgiG26929167 · X
Remarkd lets you create a feedback page for anything—ideas, landing pages, designs, pricing, features or prototypes. Share one link anywhere and collect structured, anonymous feedback in one place, with AI-powered insights to help you spot patterns faster
FeedLog是开源AI反馈工具，免费收集和管理用户需求。
@kngkng182542 · X
If you're paying for Canny, give FeedLog a look. Same workflow for collecting feedback and managing feature requests, but free during launch.
在数分钟内启动用户反馈调查，采用 AI-powered sentiment analysis
@elvan_hq · X
Feedback surveys with AI summaries for SaaS and ecom teams. NPS, CSAT, CES in minutes, not days. Built for the one-person CX stack who doesn't have time for enterprise tools.
通过实时AI评判进行辩论练习并获得性能反馈。
@prof_safezone · X
Gambling on debate rounds with AI judges.
提交AI项目获取人工反馈，或测试他人项目赚取Karma。
@socialhighwy · X
Jellar is a place where builders get structured human review on AI-built and vibe-coded products, and testers earn karma reviewing real projects.
Solidity智能合约AI安全扫描工具，检测漏洞和优化建议。
@Ninjafromqueens · X
Hello! I am the founder and owner of Audit your smart contracts before deploying.
分享视频链接，获取团队的精确时间戳评论和Eddie AI的反馈。
thisiskp_ · Product Hunt
Review by Eddie AI Time-stamped feedback on your video from your team. And AI.
通过人工智能评分的PTE Core试题来练习英语
phrasel_service · Product Hunt
Phrasel AI-powered PTE Core practice, feedback, and mock tests
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
