Chatter

We went from "works with Discord and GitHub" to "works with the channels gaming and app companies actually care about." Steam Reviews & Discussions Connect your Steam app and pull in player reviews and forum discussions automatically. No more manually checking Steam every morning to see if someone's mad. App Store Reviews iOS and Android reviews now flow in. Same clustering, same pain point grouping. Works for any app with a public listing. Sync Status & History You can now actually see what's happening with your integrations. Last sync time, messages processed, errors. Plus a log of past syncs when something looks off. Data Quality Protection First-time syncs now have guardrails. We check for test channels, bot spam, and internal chatter before anything hits your pain points. Bad early data corrupts your clusters and it's hard to fix. Auto-Translation Feedback in other languages gets translated before clustering. Your Japanese and German users' complaints now group by actual topic instead of sitting in a separate language silo. Simplified Pricing Killed the middle tiers. It's now Free (get started, see if it clicks) and Pro at $49/mo (everything, no limits that matter). The old tiers were confusing. Coming Soon Zendesk and Intercom integrations are next. AI-powered search across all feedback. Community solutions detection (surfacing when users solve each other's problems). Questions? [email protected]

The first time I pulled usage costs after running Chatter for 24 hours, I saw $2.30, and my stomach dropped. That's $70/month. $840/year. For just one instance. I'd done some napkin math, so I knew in my gut it was probably a bug, but it still scared me. Turns out it was only partially a bug. The rest was me needing to challenge my own thinking on how I built this thing. I spent the next couple days ripping it apart. Making changes, testing with live data, checking results, trying again. What I found was that I was sending API requests too often and not optimizing what I was sending and receiving. Here's what actually moved the needle, roughly big to small (besides that bug that was a dollar a day alone): • Dropped Claude Sonnet entirely - tested both models on the same data, Haiku actually performed better at a third of the cost • Started batching everything - hourly calls were a money fire • Filter before the AI - "lol" and "thanks" are a lot of online chatter. I was paying AI to tell me that's not feedback. That said, I still process agreements like "+1" and "me too." • Shorter outputs - "H/M/L" instead of "high/medium/low", as well as a 40-char title recommendation. • Strip code snippets before processing - it's just reiterating the issue and bloating the call. End of the week: pennies a day. Same quality (I've triple checked that). I'm not building a VC-backed app that can run at a loss for years. I'm unemployed, trying to build something I'm passionate about that might also pay rent. The math has to work from day one. The upside: these savings let me 3x my pricing tier limits and add intermittent quality checks to make sure feedback is landing in the right place. Headroom I wouldn't have had otherwise. Happy to answer any questions for folks running into similar