Jumprun – AI-powered research as interactive canvases

Hacker News

Hey HN! We're super excited to share our labor of love, Jumprun, which we've just opened up to everyone to try for free. Jumprun is an AI-powered research tool that whips up stunning, interactive canvases. It can dive into websites, YouTube, X, and more. You can keep your canvases fresh with scheduled daily updates, and share them with the world. Check out some cool canvases we've whipped up: - Gleam language news: https://jumprun.ai/share/canvas/01HSM7G0TBYTJWDYRFET16DFJQ - Cybertruck reviews: https://jumprun.ai/share/canvas/01HSKTGQEGB58Y1BABY0KRRAQ0 - Apple Vision Pro reviews: https://jumprun.ai/share/canvas/01HNXB2K3GM7KPRP45Y2CVVJSC - Things to do in San Francisco: https://jumprun.ai/share/canvas/01HSPRS3YXXJ9TV90P18MBZRPS Jumprun was in closed beta for a bit because GPT4-Turbo was burning a hole in our pockets. But when Anthropic dropped Claude3 Haiku and Sonnet, we saw an opportunity to use them to slash costs and get Jumprun out to all of you. We're now rocking Haiku for research and Sonnet for the final "analysis," and the results are pretty great. We even think they might be better than GPT4-Turbo! If you've got any technical questions, fire away! We're currently trying to nail down product-market fit and figure out where to focus re: features and use cases. We'd love to hear your thoughts! Thanks a ton! - Ben and Rico

Visit product View on Hacker NewsMar 24, 2024

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

84%84% 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 · Missing: supports, reddit linkedin, podcasting

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

61%61% 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 · Strong signals: reviews · Missing: plus, platform, intuitive

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

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

29%29% 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

12%12% 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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