Synnote – AI That Turns Notes into Action

Hacker News

Hi HN, I built Synnote because I kept writing pages of notes from lectures and meetings and then never acting on them. I wanted a tool that not only stores notes but actually helps me do something with them. Synnote analyses your writing, summarises key points, pulls out to-dos and can turn a note into a podcast so you can listen when you're on the move. Here's the backstory: earlier this year I was preparing for an exam and realised my notes had turned into procrastination—copying slides. I started working on a note workspace that would nudge me to act. After a few prototypes, I got something that turned my notes into tasks and summaries automatically. Friends who tried it either loved it or joked that it encourages laziness because the tool does the thinking for you. Personally, I think tools like this are about freeing up mental bandwidth, not making you avoid work. I'd love your feedback on whether this kind of automation is useful or if it feels like overkill. Does having tasks extracted for you help you focus, or does it take away too much friction? Happy to answer questions and share more details. Thanks! Here's an interactive demo you can try before using the app - https://app.arcade.software/share/Qr3QuQ3Lht1k8xN7wuGC

Visit product View on Hacker NewsOct 26, 2025

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Launch Intel predictions

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

90%90% 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: started · Missing: supports, reddit linkedin, podcasting

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · 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.

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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · 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 · Missing: web3, chat, crypto

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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