Voklit – Cheap international calls without the carrier markup

Hacker News

I built Voklit because I was tired of paying $2+/min to call banks and airlines overseas. Needed a US number that works anywhere with actual affordable rates. It's a web-based VoIP service (mobile apps coming soon). You get a real US phone number, pay-as-you-go minutes on top of a small subscription that covers the infrastructure. Bootstrapped, solo founder. Built with [Go/Next.js/ and Websockets] if anyone's curious about the stack. Adding more countries soon. Happy to answer questions or hear feedback.

Visit product View on Hacker NewsDec 24, 2025

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

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

36%36% 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.

Correct prediction on native model

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