Nomad Hypertext, a local first writing app built around semantic search

Hacker News

Nomad Hypertext is a writing app built around semantic search. It lets you see connections between your ideas in real time as your write - click on the # symbol next to a paragraph, and similar ideas you've written about in the past will show in the sidebar. This helps you spot both recurring themes and unexpected links between seemingly different ideas. It does this by generating embeddings using a local model (supabase's gte-small model) and finds similar posts with @OramaSearch, a local vector DB.

Visit product View on Hacker NewsJan 23, 2024

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

89%89% 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: ide, io · Missing: https docs, excited, just released

64%64% 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: para · Missing: mobile apps, ios, personal

47%47% 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

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

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

39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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