Baseline not captured
Baymax can guide general next steps, but personal targets stay locked until the minimum baseline is entered.
Baymax can guide general next steps, but personal targets stay locked until the minimum baseline is entered.
One useful action first: capture current measurements and routine. Do not start with an aggressive deficit.
Resume condition: complete the baseline in Today. Secure persistence is a separate gate and does not block this session.
No target calories are created until this baseline is sufficient. These fields are session-only in M0.
Use plain language. M0 stores entries only for this session.
Baymax starts with ordinary Indian meals: protein at each main meal, vegetables/fruit/fibre, mostly whole foods, and portions adjusted from real progress rather than a crash diet.
AYU’s default full-body pattern is squat/lunge, hinge, push, pull and core/carry. Progress load, reps or difficulty only when recovery and technique support it.
No automatic 10,000-step rule. Baymax progressively increases walking/activity from what you actually do, with short post-meal walks as an easy option.
Baseline weight and waist will appear here after onboarding. Longitudinal trend requires accepted persistent storage.
AYU’s existing Photo-First Body Intelligence remains part of this mission. M0 does not upload new body images because secure personal-health evidence storage must be accepted first.
Appropriate trend + good recovery → preserve the plan. Genuine plateau + good adherence → small adjustment. Fast loss + poor recovery/performance → reduce aggressiveness. Adherence blocker → fix the blocker first.
AYU extracts schemas, blocker patterns and decision logic—not your personal health payload—into the reusable Weight Management Core.
AYU may support general wellness, weight management, preparation and follow-through. It must keep user report, device observation, model inference, medical evidence and clinician judgment distinct.
Medication changes, treatment decisions, severe symptoms, pregnancy-related concerns, major disease constraints, eating-disorder concerns and other clinically material situations require appropriate professional involvement.
Shared ZUNO infrastructure does not give unrelated PH domains access to personal health data. Blockchain-capable provenance may attest privacy-preserving eligible events, never expose raw health payloads on-chain.