ChronoFlow – Automates the interview scheduling and coordination

Hacker News

Hi HN Fam, I am excited to share ChronoFlow.ai with you all. It is a tool for recruiters to automate interview scheduling and coordination between Hiring Manager and Recruiter. It speeds up the recruitment process 2x. Mostly recruiters are working manually using excel sheets, gmail for sending resumes and their data is spread in different places, thus making it hard to keep track of all the candidates. Recruiters and hiring managers using their dashboards keep track of all the shortlisted candidates, send email and schedule interviews from a single interface. It integrates with any ATS to let the customers feel comfortable with using their own ATS, schedule MS Teams call and reflect it on Hiring Manager's Outlook calendar. Thus making it a super convenient tool for the recruitment process. I look forward to your feedback to bring in improvements. Thank you.

Visit product View on Hacker NewsJul 18, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, single, using · Missing: mac, agents, macos

82%82% 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

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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