ZK

ZK Visualizer – I built this while learning zero-knowledge proofs

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ZK Visualizer – I built this while learning zero-knowledge proofs

I was learning ZK proofs and found that visualizing things really helped me understand them. Noticed there aren't many interactive visualizations out there, so I built one. Here's the first version: zkvisualizer.com It walks through the full pipeline step by step (Problem → Circuit → R1CS → Polynomials → Witness → Proof → Verification) with real Groth16 proofs generated in your browser using snarkjs. You can toggle between what the prover knows vs what the verifier sees, and there's a tamper detection demo where you can watch verification fail. This is still very early on, but I would be very happy to receive any feedback!

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Actual performance

5points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: pipe, io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: visual, using · Missing: mac, agents, macos
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: visualize · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · 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 · Missing: web3, chat, crypto
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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