Surrealist

Surrealist

Product Hunt

Build smarter knowledge graphs for data-rich applications

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Actual performance

343upvotes
50comments
Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Strong signals: smart · Missing: web3, chat, crypto
72%72% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
28%28% 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
24%24% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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