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Built a Tool to Eliminate Stripe's Invoicing Fee – PayVoice

Hacker News

Built a Tool to Eliminate Stripe's Invoicing Fee – PayVoice

Hi all! I created PayVoice to help businesses avoid Stripe's 0.4% invoicing fee while simplifying the invoicing process. Many businesses are spending extra money on Stripe invoices and dealing with manual work. I wanted to provide a more cost-effective and automated solution. With PayVoice, customers can generate, edit, and download invoices themselves—saving time and reducing customer support demands. What makes PayVoice stand out is our competitive pricing and the ability to automate invoicing using API. Here are some of the key features: 1-minute no-code setup Self-serve invoicing to reduce support No more 0.4% Stripe invoicing fee Automate invoicing with API support More affordable compared to other tools PayVoice securely connects to Stripe using Restricted API keys, ensuring your data is protected while streamlining invoicing. I’d love to hear your thoughts, feedback, and any suggestions on how to make PayVoice even better! Thank you! — Khushhal

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Actual performance

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
85%85% 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: stripe, using, code · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
41%41% 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
37%37% 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
18%18% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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