Clientpulse

Hey Product Hunt! Super excited to launch the first version of Clientpulse! 🥳 We put lots of thought and intention into making this. We know that building a great product starts with understanding your customers — but this gets really hard at scale. When you have thousands of support tickets, reviews, and surveys, you might feel like you have some evidence of what users are asking for, but there's no quantifiable insight to back it up. I've been there. As a PM, I worked on customer support automation at a 20M MAU app and struggled with the same thing: – User interviews only capture a fraction of the full picture and take lots of time – Generic AI summaries miss critical details – Traditional clustering is outdated and lacks flexibility – Existing services are too expensive to try So we built Clientpulse: an LLM-powered clustering engine that turns unstructured feedback into clear, actionable topics. The first version includes: → Automatic tagging of support tickets. → Quantitative insights on recurring issues, product questions, and feature requests. → Drill-down into real user conversations to find root causes. → Adaptive topic modeling that evolves as customer queries change over time. We're gradually onboarding first users and testing analytics for reviews and other sources with early customers. So if you're working with large volumes of customer feedback, would love to chat and hear your thoughts!