I made a tool lets you hotswap tools on your Web AI Chatbot/Voicebot

Hacker News

took about 10 months of hard work to get here, but now you can: A. create a Chatbot/Voicebot B. create databases, tools, integrations & they are fully hotswappable b/w the chatbots & voicebots C. put them on your site (or for the voicebot case you can put it on your site or use a Twilio Phone number) D. for websites, it will automatically track what pages users visit w/ revenue attribution if you add Stripe API Key - for voicebots it will record the call which you can play back on the bots dashboard E. (Extra) you can also set up a "Cloud PBX" Twilio Number that can route to an AI Agent or it can forward the call to you directly (I use this on my phone) you can test here: +1 256 588 3299 Tell me what you guys think!

Visit product View on Hacker NewsMar 18, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: agent, user, stripe · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: month, users · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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