EatingAI is a voice-first nutrition companion that turns meal tracking into a short conversation with a mascot called AO, aiming to reduce the friction of classic food diaries. The pitch is “Duolingo for nutrition”: quick daily check-ins, small corrections, and consistency-focused habit formation rather than obsessive manual entry. https://eatingai.com/
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The core interaction is a conversational UX: automatic speech recognition (ASR) captures what you ate, natural-language understanding maps it to structured foods and portions, and a nutrition database can translate that into estimated macros plus pattern-level signals (protein distribution, fiber density, ultra-processed frequency). The app also leans into multimodal capture (voice and photo) and then closes the loop with feedback, tips, and reminders that feel closer to a chat agent than a spreadsheet today.
In the interview, the team says the app is already live on the App Store and Google Play, and that they launched only a couple of days before the event to put it in real hands and watch where users get stuck. They’re building from Chișinău (Moldova) with a London HQ, and were talking about raising €500K to fund iteration, onboarding polish, and data-quality work that matters a lot in nutrition coaching here.
This space is crowded, and the hard parts aren’t just model choice: it’s measurement error, bias toward calorie-restriction, and handling sensitive health data responsibly (clear “not medical advice” boundaries, privacy-by-design, and sensible defaults). The conversation was recorded at Web Summit Lisbon 2025, and it’s a good snapshot of how voice agents, gamified nudges, and personalization are being combined to make nutrition logging feel lighter while still staying useful in a real day-to-day video.
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