Minutes – Simplifying sales call summaries and follow-ups

Hacker News

Hey everyone, I wanted to share something I've been working on that I think could be really helpful for sales teams. As an entrepreneur who handles sales and marketing, I noticed a common challenge: the amount of time managers spend on creating call summaries and writing follow-up emails. Not only is it time-consuming, but it's also often a hassle to ensure accuracy. To tackle this issue, I decided to delve deeper and spoke with several sales directors. Turns out, this problem is widespread, and even salespeople themselves dislike the administrative burden it brings. Inspired by these insights, I created Minutes. Minutes is a startup that utilizes OpenAI technology to automate the transcription and summarization of sales calls. Here's where you come in. Sign up for Minutes using the code "minutes_alpha," and you'll receive 60 free transcription minutes to play with the service. I genuinely value your feedback and insights, as they will help us refine Minutes and tailor it to the specific needs of sales teams everywhere. Thank you for your support, and I'm eagerly looking forward to hearing your thoughts. Warm regards, Bogdan, founder of Minutes

Visit product View on Hacker NewsMay 24, 2023

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

79%79% 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: email, openai, using · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

37%37% 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

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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