We built cursor for video editing

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Hi HN, We're two final-year college students from India, and we just launched FastCut – an AI tool to help creators, coaches, and marketers quickly edit there short form content (Reels, Shorts, TikToks) to make it more engaging. The goal is simple: Let users upload a raw video and get back a polished, engaging short in minutes — without touching a timeline. FastCut does the following: Automatically trims silences and filler content - Adds clean, animated captions using speech-to-text - Enhances audio - Pulls in relevant images (via Google Search), stock clips, stickers, and GIFs - Adds emojis and sound effects to make the video more dynamic We were frustrated with how much time and effort it took to make short videos look decent — so we built FastCut. This is our first real SaaS product, and we're still figuring things out. We're aware there’s a lot to improve, both in the product and on the landing page. So: We’d love your thoughts. Try breaking it. Tell us what doesn’t work, what feels off, what’s missing, or what you'd expect from a tool like this. Website: fastcutai.co We're here to learn and improve. Thanks for reading!

Visit product View on Hacker NewsApr 24, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, google, user · Missing: mac, agents, macos

95%95% 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

90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, google, users · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

43%43% predicted probability of success on AppSumo, 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

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · 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 · Strong signals: audio · 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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