Designed AI-based performance review writer

Hacker News

OpenHR AI is an AI-powered performance review platform that uses your voice to generate personalized performance reviews. We want to build delightful experience for boring HR workflows that you'll enjoy doing. And we want to keep it open source. We've put a great deal of attention and care to cut down the time it will take for you write prompts, get the output in right format, and generate high-quality performance reviews. This tool is for busy professionals who want to write better performance in minutes. Not hours. Github Repo: https://github.com/ajitesh123/auto-review-ai ps: this is one of those with "open" in name and is open source (unlike OpenAI, OpenTable, OpenText ...)

Visit product View on Hacker NewsDec 13, 2024

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Launch Intel predictions

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

83%83% 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, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

42%42% 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 · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

33%33% 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

14%14% 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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