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Textideo – Generate short AI videos from text prompts

Hacker News

Textideo – Generate short AI videos from text prompts

Hi HN, I’m Lily, a solo indie maker, and I’ve been working on Textideo — an AI video generator that turns text prompts into short videos. Why I built this I’ve always found creating videos challenging. Traditional editing tools are heavy, expensive, and require skill. On the other hand, most AI tools I tried were either locked behind subscriptions or required publishing outputs publicly. I wanted something simple: pay-as-you-go, private, and accessible to anyone. How it works You enter a short text prompt (e.g., “A cat walking on the grass at sunset”). The system runs it through multiple text-to-video models (Google Veo 3, WAN, etc.). Within 30–60 seconds, you get a short MP4 clip you can download. No subscription, no login required for trying the demo. Under the hood: Backend is built with Python (FastAPI) + PyTorch + FFmpeg for video rendering. Frontend is in React + Tailwind, optimized for minimal UI friction. Videos are generated via a credits system instead of recurring payments. What’s different No subscription lock-in — buy credits only when you need. Privacy first — you don’t need to make your outputs public. Multiple models in one place — test different AI video generators without juggling accounts. Current status The project is in beta. You can try generating a short video right on the homepage. I’d love to hear your feedback — technical, UX, or ideas for improvement. https://textideo.com Thanks for reading, and I’m happy to answer any questions!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, google, models · Missing: mac, agents, macos
62%62% 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
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, google, way · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: recurring, subscription · Missing: arr, mrr, revenue
26%26% predicted probability of success on Acquire.com, 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
13%13% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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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