ccMarvin – Just Email with AI

Hacker News

Backstory: My name is Michael Stoppelman, I'm a super angel (300+ investments, I've invested in YC companies like Vanta, Flexport, Biorender, Permitflow and Canary Technologies). Prior to that I built and ran the engineering team at Yelp. I thought there was a missing piece to the LLMs where they couldn't talk via email which is where as an investor I work all day. So I built ccMarvin so I could forward emails for summaries, I could get legal feedback on SAFEs or other transactional emails, I could get newsletters on sectors like AI / Space or specific folks I want to follow. I don't like to use X because I end up getting to sucked in and waste time doom scrolling, I rather get a newsletter. So I'm announcing ccMarvin: a service you can just email at marvin@ccmarvin.com. It's like emailing a very smart research analyst or chief of staff that's connected to all the LLMs (Gemini / Claude / ChatGPT & xAI). I've embedded some investor friendly features for tracking your private / public investments via X and other news sources or you can create custom newsletters. Example emails to send marvin@ccmarvin.com: "Send me an email everyday Monday on the top AI stories for the previous week." "Create a newsletter everyday that I get at 7am of what @elonmusk and @sama saying yesterday on X" "Can you track SpaceX, Anthropic, and Google news everyday, send me a portfolio update everday at 6am" Check it out and leave some feedback.

Visit product View on Hacker NewsJun 24, 2026

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Launch Intel predictions

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

94%94% 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 · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% 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: friendly · Missing: plus, platform, intuitive

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

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

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

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% 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, smart · Missing: web3, crypto, cryptocurrency

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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