Launched this week
Your feedback is everywhere — Slack threads, Intercom support tickets, review sites, DMs. ProductBridge's AI agent collects it all automatically, organizes it, deduplicates, and helps your team ship what users actually want. Users request features, upvote, and watch ideas move through your public roadmap. Teams prioritize with data, publish changelogs, and auto-notify users when their feature ships. One platform. Complete feedback loop. Flat pricing. No seat fees. No surprises. Ever.
We collect client feedback across several channels at once — and deduplication is what interests me most. The same request often arrives three times, worded differently, and it's hard to tell if it's one problem or three. How does ProductBridge decide two pieces of feedback actually belong together?
ProductBridge
Great question @klara_minarikova — this is core to how ProductBridge works.
We use advanced RAG + LLM to match feedback by intent, not just wording. But the real differentiator is context — our AI already knows your full board. Knowledgebase, existing feedback posts, what's on your roadmap, what you've already shipped in the changelog.
So if someone requests something you launched 2 months ago, it knows. If 3 people describe the same problem differently, it groups them.
Timelaps
Hey Hareesh, congrats on the launch! Interesting tool solving a real problem.
Question: Feedback online is highly skewed and biased (as it takes particular types of personas to post, with no proper way to 'control' via experimental design). Is a product roadmap built on online feedback the best path forward for builders?
ProductBridge
@harryzhangs Thanks for the support! and honestly, it's a fair challenge!
ProductBridge helps in two ways: user tagging with MRR and revenue data means you weigh who's asking, not just how many. And pulling from multiple channels — tickets, Slack, emails — broadens the signal beyond just the people who bother to post.
This is a very interesting idea. In our business, we receive a lot of feedback from multiple channels that never really gets processed as data as such, so this idea could actually be relevant, but I have a couple of doubts that came to mind:
The actionable insights sound great, but how does the app process contradictory feedback from clients to decide which side to lean to? Is there a process of prioritizing certain types of feedback over others? It would be super interesting to get a bit more info about this.
Anyways, congratulations for the launch!
ProductBridge
@carlos_alfredo_davila_aguilar Thank you! Really glad it resonates.
On contradictory feedback: ProductBridge doesn't pick a side automatically. Instead it shows you the full picture — how many people said what, and who they are. That context is what helps you make the call.
On prioritization: it's not just vote counts. You can tag users with properties like MRR or plan type. So if 10 free users want one thing and 3 paying customers want the opposite, you can see that clearly and decide what actually matters for your business.
The goal is to give you better information. 🙌
@hareesh_vemasani Thanks for your reply Hareesh! This actually clarifies my doubt.
timing is everything with this. built something myself and the biggest mistake was collecting feedback too late. question: does it consolidate across app store reviews too or mainly social/community platforms
ProductBridge
@renkethye 100% — feedback collected too late is almost as bad as no feedback at all.
App store reviews — great timing on the question! We support Slack, Intercom, support tickets and more right now. App store integration is coming in the next couple of weeks. It's high on our list and almost there.
Stay tuned — and thanks for the kind words! 🚀
How does the deduplication work when users describe the same issue in completely different words? Congrats on the launch!
ProductBridge
@borrellr_ Thanks! 🙌
Our dedup works at the intent level, not keywords. We use advanced RAG + LLM, so "the app is slow" and "keeps timing out" get grouped correctly even though they share zero common words.
The AI also has full context — your existing feedback, roadmap, and changelog — so it's matching against everything, not just other incoming posts. And nothing merges without your review. 🚀
TruGen AI
Congrats on the launch! @hareesh_vemasani @rohithreddy
Honestly, this is something most teams just deal with instead of solving.
Feedback keeps coming in, but it rarely turns into clear product decisions.
Really like how you’ve made it more structured and usable.
Curious, what kind of feedback patterns surprised you the most so far?
ProductBridge
Thank you so much! 🙌 @bhavyasree
Biggest surprise: teams discovering that the same problem had been reported 12+ times — just never connected. Different words, different channels, different teammates receiving it. Once it's all in one place, the priorities become obvious really fast.
NOVA
Feedback is everywhere — support tickets, Slack, emails, user calls, but turning it into clear, actionable insights is still a big challenge for most teams.
ProductBridge seems to be tackling exactly that gap. If done well, this could really help teams prioritize better and build what users actually need.
Curious, how does ProductBridge handle deduplicating and prioritizing feedback across different sources?
Congrats on the launch and excited to see how this evolves 🚀
ProductBridge
Thank you, @dharmikp1908! 🙌 You've described the problem perfectly.
On dedup: we use advanced RAG + LLM, so matching happens at the intent level, not keywords. The AI already knows your full context — knowledgebase, existing feedback boards, roadmap, and changelog. So the same problem coming in from Slack, a support ticket, and an email gets grouped correctly, even if the wording is completely different.
On prioritization: it's not just vote counts. Users can be tagged with properties like MRR and revenue tier, so you're always seeing who is asking, not just how many.
Really excited to build this out further — appreciate the support! 🚀