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Open Vernacular AI Kit – preprocessing for Indian code-mixed text

Hacker News

Open Vernacular AI Kit – preprocessing for Indian code-mixed text

Built an OSS toolkit to normalize mixed-script/mixed-language user text before LLM pipelines. Focus is production use: API mode, Docker deploy path, language-pack interface, and evaluation snapshots. Would appreciate feedback on data strategy, evaluation design, and integration patterns. https://github.com/SudhirGadhvi/open-vernacular-ai-kit

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, dock, code · Missing: mac, agents, macos
71%71% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, pipe, io · Missing: https docs, excited, just released
44%44% 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
43%43% 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
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
15%15% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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