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.
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! 🚀
Zennbox
Feedbacks are like goldmine, just curious how will ProductBridge will filter out feedbacks from tons of other contents. Congratulations on the launch. This looks a great product that will genuinely help businesses.
ProductBridge
@bhu_1 Love that analogy — goldmine is exactly right. The problem is most teams are digging with their bare hands! :)
ProductBridge uses AI to separate real feedback from noise at every step. When feedback comes in from any channel — Slack, support tickets, emails — the AI classifies it automatically. Duplicates get grouped.
What's left is clean, structured, actionable signal. No manual sorting needed. 🙌 Thank you for the kind words!
Bringing feedback from multiple channels into one place and actually turning it into roadmap decisions sounds really useful. I like the focus on closing the loop with users after features ship. How does ProductBridge detect and merge duplicate feedback across different sources without losing important context?
ProductBridge
@vik_sh Thank you! Great question — and the "without losing context" part is key.
We use RAG + LLM to match feedback by intent, not keywords. So the same problem described differently across Slack, support tickets, and email still gets grouped correctly.
You see the full picture: how many people raised it, what they said, which channel it came from. Nothing gets lost, just organized.
If the feedback agent is not enough confident on the grouping, it will flag it for the review. 🙌
Paperguide
Congratulations on the launch.
The signup and onboarding flow feels very clean and intuitive. I was able to quickly understand what to expect after signing up, which made the initial experience seamless.
The ability to integrate and collect feedback across multiple channels automatically addresses a major pain point. From my own experience managing different customer support channels and aligning them with the product roadmap, it’s easy to miss requests and it can become quite time-consuming. This approach seems to significantly streamline that process.
I’m curious if there are plans to extend this further into customer support workflows. For example, enabling an embeddable chat interface on a website where the AI agent can reference the knowledge base, roadmap, and feedback tickets to respond to users, and seamlessly hand off to the support team when needed.
Overall, this looks like a very promising product.
ProductBridge
@yash2110 Thank you Yashwanth — really glad the onboarding felt seamless, that was something we obsessed over! 🙌
The vision for ProductBridge has always been to be a complete product management and customer support platform — not just a feedback collector.
An embeddable AI chat that references your knowledge base, roadmap, and feedback tickets — and hands off to a human when needed — is something we're actively building. Customer support chat is on our roadmap and coming soon.
Really appreciate the thoughtful feedback — and excited to have you try it when it lands! 🚀
Took a quick look, initially it felt like a familiar feedback tool.
What clicked for me a bit later was the 'pulling feedback from everywhere automatically' part. That feels like the real shift.
Made me wonder if people usually get that right away, or if it takes a second like it did for me?
When users are notified after shipping, how do you avoid sending irrelevant updates to people whose requests only partially match?