Positioning
Mineral Balance Diet is not a language model and not a “recommendation engine”. It is a constraint‑based Physical AI system that operates inside biological systems—by producing a daily executable plan aligned with standards and mineral stability domains.
The missing infrastructure
Nutrition standards (RDA/DRI) have existed for a long time—but they were never engineered into an execution system that can run daily for ordinary people.
- Before: advice, content, tracking, expert guidance (hard to scale).
- Now: objectives + constraints + solver + daily executable outputs.
What makes it hard (and why compute alone doesn’t solve it)
The core difficulty is not “more compute”. It is the cross‑domain engineering of:
- homeostasis as an engineering objective
- nutrition standards as measurable constraints
- mineral balance stability domains as tighter constraints
- real foods + grams as executable variables
- edge execution (phone) for daily reliability and privacy
What we built
- Objective: meet nutrition standards (RDA/DRI).
- Constraints: operate inside mineral balance stability domains.
- Variables: real foods and grams.
- Output: a unique, executable daily meal plan.
Not “suggestions” — an engineering solution that runs daily.
Distribution as infrastructure
- Everyone has it: it runs on phones.
- Everyone needs it daily: food is a daily necessity.
- Network effects (optional): WebRTC can connect families/friends so executable results flow through real relationships.
What an IC will question (and how we answer)
1) “Why hasn’t anyone done this before?”
Because it requires a single integrated system across nutrition science, optimization, and product engineering. A “content” or “LLM” approach can’t guarantee constraint satisfaction; a “compute” approach alone can’t define the right constraints or stable domains.
2) “Is this medical?”
No. It operates on lifestyle execution. It does not diagnose, treat, or replace clinicians. It outputs standards‑aligned meal plans and trend‑oriented stability indicators.
3) “Where is the moat?”
Moat comes from the engineered constraint system, solver design, stability domain definitions, and daily execution reliability on edge devices—plus the learning loop enabled by iterative user adjustments.
Why invest now
You are buying “time before infrastructure becomes obvious”. The goal is to protect long‑term engineering cadence, avoid short‑term monetization distortion, and reach an irreplaceable infrastructure position.