Memable.ai: Your Personal Recall Companion

Hacker News

Hey HN, Ever felt overwhelmed by the sea of information online, and frustrated when you can't recall that great idea you came across? This has been my story for as long as I can remember, so I went about building something to solve this: memable.ai Why Memable? - It’s like a super-bookmark, not just saving links, but also capturing the ideas themselves, making them easy to recall and explore. - It’s a single space to house all your interesting finds, no matter where you found them—be it Twitter, a blog post, or Reddit, and more. - It aids in effective recall through conversations initiated by your AI and connecting diverse ideas, fostering creative thinking. Key Features: - Automatically summarizes and extracts core ideas from websites, blogs, and soon, more formats like e-books and videos. - Comes with an AI companion to chat and help explore ideas and recall content based on your memory pattern. - Offers a unique navigation experience through your "map of ideas" based on their meanings and connections. After months of hacking in my spare time, I’m thrilled to share this with the community and is currently free to use. I’m all ears for your thoughts, feedback, or suggestions. Let's make learning and recalling fun and effective together!

Visit product View on Hacker NewsSep 30, 2023

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

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best fitHighest predicted score across all platforms for this description.

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

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: soon · Missing: plus, platform, intuitive

63%63% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

51%51% 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: personal, video, month · Missing: mobile apps, ios, entrepreneurs

34%34% 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

11%11% 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

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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