ProductBridge
AI-native customer support and feedback agent
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ProductBridge - AI-native customer support and feedback agent

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Most teams run a helpdesk, a feedback board and a survey tool, then copy between them all week. ProductBridge is one system. An AI agent answers support chats from your help center, calls your APIs via tools, workflows and MCP, and hands off when it should. Every chat, survey and vote is captured, deduplicated and scored by reach and revenue, so your roadmap runs on evidence, not opinions. Ship it and everyone who asked is notified. MCP for Claude, ChatGPT and Cursor. Flat pricing, free plan.

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Maker
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Hey Product Hunt 👋 Hareesh here, founder of ProductBridge. In March we launched here as an AI agent that collects feedback from Slack, Intercom, review sites and your feedback board, merges the duplicates, and turns the pile into a roadmap. You sent it to #1 for the day. Thank you for that 🙏 We spent the six months since watching how teams actually used it, and one pattern kept showing up: the feature request almost never started on the feedback board. It started as a support conversation, in a different tool, attached to a different customer record. Support saw it first, product saw it last, and nobody told the customer when it shipped. So we built the other half. ProductBridge is now AI-native customer support and feedback on one customer record: 💬 Live chat + shared inbox — chat and email together, with assignments, SLAs and CSAT 🤖 AI support agent — grounded on your help center, calls your APIs through tools and workflows, and hands off to a human when it should 📚 Help center — write an article once and the agent answers from it 📊 Surveys — NPS, CSAT and CES inside your product, with responses flowing into the same feedback intelligence 🔌 MCP server — 36 tools, so you can ask Claude, ChatGPT or Cursor what your customers are asking for 🔁 The same closed loop as before — a support chat becomes a feature request, gets scored by reach and revenue, and the customer who asked is notified when it ships What hasn't changed: flat price. No per-seat, no per-tracked-user, no per-resolution fees. There's a free plan, most teams are live in about 15 minutes, and if you're on Canny, Featurebase or Intercom we'll help you move. One question for you 👇 What's the one thing your support + feedback stack still makes you copy-paste by hand? That's usually where we find the next thing to build. I'll be here all day answering questions 🚀
🧐 Good find

 Congrats on the launch.. the problem space you're tackling is a massive headache for most startups

Maker

 So true! Having more tools without sharing the context is always a problem for organizations. ProductBridge comes with tools that required to manage the customer support + feedback + surveys at one place - so that the context always shared.

 nice launch! the closed loops approach are the really interesting and also the MCP servers with 36 tools cought my attention,

how well does this work with the clone requests???

Maker

 Thank you, ! If by clone requests you mean duplicate or closely related feedback, ProductBridge detects and groups them into one request while retaining every customer, vote, and original conversation behind it.

When the request moves forward or ships, everyone linked to it can be notified—closing the loop without manually tracking each duplicate.

 Does the agent learn from past support conversations and feedback support ?

Maker

 Yes! The agent uses past support conversations, customer feedback, help-center articles, your knowledge base, roadmaps, and changelogs as context when responding.

Maker

 It doesn’t retrain the underlying model; instead, its answers stay grounded in the latest information available in your ProductBridge workspace - your feedback items, roadmap, changelogs, support conversations, help center articles and knowledge base it is trained on.

 congrats on the launch! Wish you the best with it.

 Congratulations on the launch!

OpenAI
GPT-6 Astra Challenge
What real task does your product handle with GPT-6 Astra?
Maker
Our AI support agent uses GPT-6 Astra to resolve customer chats: it answers from the help center, calls the customer's APIs through tools and workflows, hands off to a human when it should, and turns each conversation into a deduplicated feature request on the roadmap.

Congrats on the launch!

Maker

 Thanks a lot, Rugma.

Congrats on the launch. Can feedback collected from Slack, Intercom, Zendesk, and other sources be linked back to the same customer automatically?

Maker

 Thank you!

Yes - when a unique identifier such as an email address or user ID is available, ProductBridge automatically links feedback from Slack, Intercom, Zendesk, and other sources to the same customer record.

This gives teams one view of the customer’s feedback and support history while preserving the original source.

🧐 Good find

Congrats on the launch , With feedback coming from support chats, surveys, and votes, how do you handle conflicting feedback from different customer segments? Can the AI help identify which insights are worth prioritizing for the roadmap?

Maker

 Thanks a lot for the support, !

ProductBridge keeps the customer segment and source attached to every piece of feedback, so teams can see where opinions agree or conflict.

The AI groups related feedback into themes and highlights signals such as reach, MRR, customer impact, and segment relevance. It helps teams understand what deserves attention, while the final roadmap decision remains with the product team.

 That makes sense! I like that the AI helps identify the important signals without taking the roadmap decision away from the product team. 🙌 Can teams customize which signals matter most based on their product goals, like retention, revenue, or enterprise customer needs?

Maker

 Yes! Teams can segment feedback by customer type, plan, or MRR and focus on what matters most. We currently rank insights by reach and impact, and custom weighting is on our roadmap.

Does the help center also act as a knowledge source for the AI support agent when answering customer questions?

Maker

 Yes, absolutely! The help center acts as a knowledge source for the AI support agent. Whenever an article is added or updated, the agent can use the latest information to answer customer questions accurately and consistently.

Maker

 Not just that, support agent also understands the existing feedback items from the customers, your planned roadmap, changelogs you have already published - and responds to customer queries with this context.

The idea of keeping support conversations and product feedback in one customer record makes a lot of sense. Congrats on the launch!

Maker

 Thank you! That’s exactly what we’re trying to solve - giving support and product teams the same customer context, so valuable insights don’t get lost between different tools.

Congrats on the launch

quick question, does the platform support SSO and role-based access for larger product and support teams?

Maker

 Thanks! 😊 Yes, we support role-based access with Owner, Admin, and Member roles. For team SSO/SAML, get in touch with us about the setup. Happy to walk through what your product and support teams need!

Loved the idea of bringing support and product feedback together. Abosoltely getting the point that a lot of useful feedback gets lost between these tools. The part about automatically grouping similar requests is pretty neat. Congrats on the launch!🫡

Maker

 Thanks so much! A good feature request shouldn’t disappear when a support chat gets closed. That’s what we’re trying to fix. Really appreciate you checking us out and supporting the launch! 🙌

Congratulations on the launch 🚀

Maker

Thanks a lot for the support, !

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