I turn scattered feedback into a prioritized roadmap in 5 min
AI duplicate detection for feedback, but Canny and Uservoice already solved this problem better.

Shows MRR at risk per feature request so you prioritize by revenue, not vote count.
Product managers and startup founders
Canny · ProductBoard · UserVoice
I’m building Resonly to help teams prioritize feature requests with more context than just votes.
The idea is simple: not every request is equal. A feature requested by multiple paying customers may matter more than one with 100 upvotes from free users.
I’ve added a way to associate revenue with each customer, so when someone upvotes or submits a feature request, the admin can see three signals:
MRR at risk — how much current MRR is tied to customers asking for it;
MRR lost — how much MRR was lost from customers who churned before it was solved;
Potential MRR — how much MRR could be converted from trial customers requesting it.
I’d love your honest feedback on the idea and positioning.
AI duplicate detection for feedback, but Canny and Uservoice already solved this problem better.
Feedback voting with AI dedup and RICE scoring—Canny and ProductBoard already do this.
Makes your coding assistant an active member of the product workflow: install the MCP server and agents can triage inboxes, surface semantic duplicates (pgvector + Voyage), suggest sprint candidates, and generate changelog drafts. Clever engineer-first positioning — the novelty is treating agents as first-class users — but I'd want stronger detail on permissions and guardrails before letting bots fully close the loop.
Impact Score concept is interesting, but Asana, Notion, and Things already own this.
Unified GitHub and GitLab inbox for teams drowning in AI-generated PRs.
Feature request, not a project — no code, just asking Mozilla to add a toggle.