Automate phone calls with AI for 2 cents a minute

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Hi folks, my partner and I just finished the MVP of a no-code AI phone automation tool called ThunderPhone. I'd love to get your thoughts. We've worked on a few phone AI projects recently, and have had a couple of persistent frustrations with tools like Retell, Vapi, etc. - namely that they're quite complicated to set up, and pretty pricy, around 10 cents a minute. After kicking the idea around for a while, we finally decided to go for it and build this. ThunderPhone costs 2 cents a minute for inbound and outbound calls, telephony charges included. It also handles a variety of integrations directly or through Make.com. We've set up templates and wizards to make it easy to set up integrations to trigger calls however you'd like, and to have phone calls read and write information dynamically to/from spreadsheets, emails, calendars, etc. This is an early release, so still lots of work to do! We'd appreciate your thoughts if you have a chance to try it out.

Visit product View on Hacker NewsApr 17, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, code · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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.

AppSumoStrong fit for a featured deal · Strong signals: calls · Missing: plus, platform, intuitive

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

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

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

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

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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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