Automated triaging, investigation and remediation of on-call issues

Hacker News

Hey HN! We're the founders of Hatchet: the copilot for your on-call incidents. Hatchet is able to integrate with your existing systems like Pagerduty, Sentry, DataDog, OpsGenie, CloudWatch, Confluence, Slack and Google Drive. Through these integrations we're able to generate a holistic view of the incident and able to inject context directly into the page. Ultimately, this capability allows on-call engineers to reduce their time-to-resolution 100x! We're opening up a closed beta this week with 10 spots, if this sounds interesting, we would love to chat more. You can book a demo with us via the link in our page: gethatchet.com or by sending us an email: andre@gethatchet.com Thanks & Cheers HN! Andre

Visit product View on Hacker NewsOct 24, 2023

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

92%92% 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 NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

43%43% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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