Ambient: AI Chief of Staff

Hacker News

Hi, i'm looking for product feedback on a new generative AI product called Ambient. We are calling it an AI Chief of Staff, and it's basically a summarizer for everything: Zoom meetings, Slack. Hubspot, Jira, delivered in a newsfeed format. Stories are threaded together with AI Tags. It's a Narrator for your business, a knowledge base for everything that doesn't go stale.

Visit product View on Hacker NewsJun 28, 2023

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Actual performance

1points

2comments

Did not reach leaderboard

Launch Intel predictions

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

87%87% 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.

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

46%46% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

40%40% 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 · Strong signals: arr · Missing: mrr, revenue, profit

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Correct prediction on native model

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