Stop guessing what users want. Audyr's AI captures feedback through conversational widgets and integrations such as Intercom, merges duplicates automatically, and tells you exactly what to build next. Used by curious product teams.
User feedback is messy. I built something to fix that.
Duplicate requests. Random comments. Scattered conversations. Making sense of it all is the hard part. I've talked to successful founders and the same frustration kept coming up: getting sorted, actionable feedback is still a pain, even when you're doing well.
So I built Audyr. My first ever SaaS, built solo as a student in Next.js with a bunch of other cool tech I will get into at another point of time.
Audyr is an AI-powered feedback widget you embed directly into your app. It automatically deduplicates feedback, analyzes sentiment, surfaces the most important insights, and lets you have real conversations with users.
I didn't build this for enterprise teams with Intercom budgets. I built it for smaller startups and indie founders who are moving fast and can't justify bloated tooling costs. At $35/month, it's priced for the teams that need it most.
I also care a lot about design. The widget is clean, minimal, and built to feel native in your product. No cockpit dashboards. Just clear, readable insights.
Audyr is live. Would love for you to check it out at audyr.com.
Curious how the conversational widget works in practice. Is it proactively prompting users mid-session based on behavior triggers, or is it more of a passive "leave feedback here" button? The difference matters a lot for response rates — passive widgets get ignored, triggered ones get gamed.
most feedback tools don't fail at collection, they fail at synthesis. you end up with a tagged backlog of requests and someone still has to sit down and figure out what any of it means for the roadmap. ai clustering helps but it usually stops at "here are your themes," which is still a judgment call away from an actual decision.
what stands out here is the conversational widget approach, where the ai is probing in context rather than just logging a freetext box. combined with cross-source deduplication across channels like intercom, by the time something surfaces it's already been validated across multiple touchpoints, not just the loudest customer's voice. that's the part that's usually still manual. :)
The claim that you tell teams what to build next is interesting. But what happens when the loudest users want something different from the silent majority — how do you weigh that?
Congrats on the launch! I feel deduplication is the feature everyone looking for feedback tools wants to see, glad to see you focused on it for Audyr 🔥
With CoreSight, we rely heavily on user feedback to understand how people interact with the analysis outputs, and the hardest part is always separating the recurring themes from the one-off requests. How does Audyr handle feedback that's phrased completely differently but is basically asking for the same thing underneath?
Sam