I spent 45 minutes driving to work every day unable to talk to my AI agent, so I built an iOS app where I can handsfree talk to my AI agent - with full TTS and STT built-in

Every morning I drive 45 minutes to work. I have an AI agent I use for planning, task management, and thinking out loud, and I couldn't use it at all during that commute. The phone-in-hand solutions weren't going to work while driving. The web UI needed tapping. So, I started building something just for myself. That was two months ago. What I ended up with is ClawVibe, a native iOS voice assistant that talks to your AI agent, completely hands-free. The problems I ran into (and why the app works the way it does) My first version streamed voice audio over the mobile network to a server for transcription. In theory, fine. In practice, latency spikes, packet loss on patchy mobile signal, the whole thing falling apart mid-sentence. I realised the core mistake: audio is a huge amount of data to push over a mobile connection reliably. Text isn't. So, I moved everything on device. The speech recognition happens on the phone. The text-to-speech happens on the phone. The only thing that ever travels over the network is the transcript, a handful of characters. Latency dropped. Packet loss became irrelevant. It even works in areas with barely any reception. Moving on device created its own problem. Most ML models want to use Apple's Metal framework (GPU acceleration) which is fast. But Apple doesn't allow Metal processes to run in the background. So as soon as the screen went off, the model would stall. I had to switch to standard CoreML without GPU acceleration to keep it running in the background while driving. Trade-off worth making. The other thing I kept hitting was background noise. GPS directions. Someone talking nearby. A radio. All of it was getting picked up and sent to the AI as if I'd said it. The fix was voice biometrics; the app now learns your voice profile and only sends audio it recognises as you. GPS can announce a turn and the AI ignores it. What I built: * On-device speech recognition: transcribed on the phone, never sent to Apple or Google. Only the text goes to your AI. * On-device TTS: multiple voice options, spoken back through the phone or CarPlay speakers. * Always-on voice detection: no button, no wake word. It knows when you're talking. * CarPlay: full hands-free in the car. The original reason I built it. * Primary voice recognition: option for only your registered voice to trigger the AI. Background voices and sounds are ignored. * GPS context: location data sent with every message for location-aware responses. Where it's at: In TestFlight beta now, and I am looking for beta testers. It will be free on the App Store after beta testing and once it clears review. The free version gives you the full core voice experience. A Premium tier is coming with a whole range of value-added features: more voices, multiple voice profiles, expanded CarPlay UI, Apple Watch support, and more. You will need your own AI backend to connect it to, it supports a few different setups, and more integrations are in progress. If you already run your own OpenClaw instance, you're good. If you don't have your own AI server set up yet, you can still trial the app with a local on-device model. If you're into self-hosted AI, privacy-first tools, or just want hands-free AI in your car, I'd love feedback. What would make this useful for you, or what would stop you from using it? And which AI system would you want to connect it to?