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I built the 'mouse' for a personal, always-on AI on your phone

Hacker News

I built the 'mouse' for a personal, always-on AI on your phone

i HN, I'm the creator of Sein. I believe the "Hey Siri" or "OK Google" model is fundamentally broken. We're forced into a 'summoning' ritual that erects a wall between us and our AI. Meanwhile, our data is sent to cloud "mainframes," where privacy is often the price of admission. The "PC revolution" for AI is here, but we're missing the 'mouse'. The "Personal Computer" is already in our pockets—our phones have powerful neural engines. What's missing is the right input device to seamlessly connect our thoughts to our own private AI. That's why I built the Sein Clip. It's not another computer; it's the 'mouse' for the Personal AI era. It’s a small wearable obsessed with one thing: capturing your voice with far greater clarity than a phone in your pocket ever could. The Clip securely sends this audio to the Sein App, where your phone becomes your private AI server. But the revolutionary part isn't just the hardware, it's the new paradigm of interaction it enables: 1. 100% Private by Default. We bring cloud-level voice and intent recognition to run entirely on your local device. Your data belongs to you, and only you. This isn't for our convenience; it’s for your protection. 2. Truly 'Always-On', No Wake Word. We tore down the wall. Our AI is designed as an "always-on" companion that uses contextual awareness to know when you're talking to it. Your thoughts are captured frictionlessly, making interaction as natural as talking to a friend. 3. Emotional Intelligence. Having solved the 'when' of interaction, we focus on the 'how'. Our AI perceives your "emotional map," understanding when to be proactive and when to be silent. It becomes a companion that assists you, not just a tool that executes commands. 4. Our Vision: Built on MCP. This is just the beginning. Our system is built on a foundational protocol (MCP) designed for an open, interconnected ecosystem of future collaborative AI experiences. The best is yet to come. The Business Model: It's simple. You buy the hardware (the "mouse"), and the companion app with all its local AI software is yours forever. An optional subscription will be for power users who choose to leverage the "mainframe" (cloud models) for specific tasks. I'm launching on Kickstarter soon and would love the HN community's feedback on this approach—that our phones are the new PCs of the AI era, and what we need now are the right peripherals to unlock their true potential. Pre-launch page: https://www.kickstarter.com/projects/sein/sein-the-first-wea...

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
86%86% 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, mcp, google · Missing: mac, agents, macos
84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, google, users · Missing: mobile apps, ios, entrepreneurs
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon, users · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
42%42% 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: subscription, active · Missing: arr, mrr, revenue
15%15% 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.

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