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ToolKuai – Privacy-first, 100% client-side media tools

Hacker News

ToolKuai – Privacy-first, 100% client-side media tools

Hi HN, I’m Linn, the creator of ToolKuai ( https://toolkuai.com ). Like many of you, I’ve always been wary of "free" online file converters. Most of them are black boxes: you upload your private documents or images to a remote server, and you have no idea where that data ends up or how it’s being used to train models. I wanted to build a suite of tools (Video/Image compressor, OCR, AI Background Remover) that runs entirely in the browser. No files ever leave your machine. The Tech Stack To make this performant enough to rival server-side processing, I leaned heavily into modern web APIs: - AI Background Removal: I'm using ONNX models (Xenova/modnet and ISNet) running locally via Transformers.js. The processing is 100% client-side, fallbacking to WASM when WebGPU isn't available. - Frontend: Built with SvelteKit (Svelte 5) for its lean footprint and fast reactivity. - Storage & Delivery: AI models are self-hosted on Cloudflare R2 to avoid massive bandwidth costs and ensure fast delivery. Current Stats (13 days in): The site is only 2 weeks old. Surprisingly, I’ve seen strong organic interest from Taiwan and Hong Kong. Average time on site is currently around 3.5 minutes, which suggests people are actually staying to process multiple files, confirming that the client-side speed is hitting the mark. Future & Monetization The tool is free. I’ve decided to avoid the "Pro/Premium" subscription model, as I believe these utility tools should be accessible. I'm exploring non-intrusive ads to cover the infrastructure costs (mostly R2 and Vercel). I’d love to get some feedback from the HN community on: - Performance on different hardware (especially the WebGPU-based video compressor). - Privacy concerns or suggestions on how to further harden the "No-Server" promise. - Any specific media tools you feel are currently lacking in the "client-side only" ecosystem. Link: https://toolkuai.com Thanks!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
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AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive
57%57% 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
37%37% 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: mac, model, models · Missing: agents, macos, agent
30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, way · Missing: mobile apps, ios, personal
28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
20%20% 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.

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