@heyayankai · X

💬 Building FeatureSay. A simple platform to collect user feedback, prioritize feature requests, and build what customers actually need.

@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.

@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

@ImFabien · X

- feedback management and suggestion box with built-in churn insights for SaaS teams.

@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.

u/Top-Quarter-4281 · Reddit

I made a product for analysing app reviews and get insights Hi folks! I recently made ParseMyApp , it takes any app and turns its reviews into something usable: top complaints with root causes, what users would riot if you removed, feature requests ranked by impact, and where competing apps could win based on analysed app weaknesses. Bonus: No account needed, free and runs entirely in your browser. How does it work: it pulls up to 500 reviews for iOS (Apple's API cap), and up to 1500

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

@axeltdesign · X

do you think this is vibe coded?