Alconost MT/ Evaluate
Indie HackersAI tool using LLMs to evaluate and improve translations
We built the tool to answer one question: Is this translation good, and how can I improve it? Powered by LLMs, it scores accuracy, fluency, and more, with clear fixes and batch processing for fast, structured reviews
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos67%67% 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, podcasting61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: reviews · Missing: plus, platform, intuitive49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, io · Missing: https docs, excited, just released31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue12%12% 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, crypto9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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