I built a professional PO file translation platform

Hacker News

After spending countless hours manually translating PO files for my websites and losing time on repetitive translation tasks, I built TranzlyWeb - a professional translation management platform that transforms hours of work into minutes. What you'll see on the site: - Upload PO files and get professional translations in minutes, not days - 15x faster than manual translation with 95% accuracy rate - Support for 50+ languages with automatic translation tools - Free plan to get started, Premium for unlimited translations ($10/month) - Project management system to organize your translation files - HTML translation tool for direct website content translation The platform handles everything from basic PO file editing to advanced translation workflows, collaboration tools, and quality assurance. You can start free with basic tools and upgrade when you need unlimited power. Key features: - Professional-grade translation management - Automatic file translation with human review options - Project organization and file management - Real-time translation progress tracking - Export translated files in multiple formats I built this because I was tired of spending 8+ hours per PO file doing manual translation work. Now the same work takes just a few minutes with professional results.

Visit product View on Hacker NewsSep 29, 2025

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

89%89% 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: tasks, project management · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

47%47% predicted probability of success on TrustMRR, 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

26%26% 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 · Missing: arr, mrr, revenue

15%15% 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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