We made an open-source AI agent to help you during your on-call shifts

Hacker News

Hey guys, We’re excited to introduce to you what we’ve been working on for the past few months. We are two co-founders and we’ve both experienced on-call shifts where we felt unprepared, the relevant people weren’t around to help or we were left in the middle of the night trying to figure out what went wrong. Merlinn is an open-source AI on-call developer that lives in Slack. It can help you alleviate some of the pains mentioned above by connecting to your favorite tools and pair with you to triage the incident. We also have a pro version that we host on our cloud. Our goal is to help companies reduce MTTR, keep your SLAs in check and improve the on-call experience. If you’re interested in what we’re doing, you can join our slack community: https://join.slack.com/t/merlinncommunity/shared_invite/zt-2... Visit our website to learn more: https://www.merlinn.co/?utm_source=hackernews That's it! If you have any questions/feedback/thoughts, we'd love to hear them :)

Visit product View on Hacker NewsJun 25, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, slack, new · Missing: mac, agents, macos

86%86% 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

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

64%64% 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: month · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% 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

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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