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WireAI
Use Case — Nutrition & Lifestyle

Food recommendations, rendered as they're generated.

User tells Wire RN their preferences and dietary context. The SDK streams back a recommendation card (ingredients, macros, preparation), built native, not templated.

Back to Dynamic Onboarding

76-second walkthrough

A preference-to-recommendation flow. Watch Wire RN build the card in real-time.

7 moments from the flow

Sampled across the 76-second session.

Wire RN food recommendation — screen 1 of 7
Wire RN food recommendation — screen 2 of 7
Wire RN food recommendation — screen 3 of 7
Wire RN food recommendation — screen 4 of 7
Wire RN food recommendation — screen 5 of 7
Wire RN food recommendation — screen 6 of 7
Wire RN food recommendation — screen 7 of 7

Architecture

How this use case maps to the stack

1

Attribution

Dietary preferences, allergies, calorie targets set at install. Meal history if available.

2

Agent layer

Phase 1: generates a meal category and ingredient set based on user profile. Phase 2: adapts the card format (macro-heavy vs. recipe-first) based on past engagement.

3

Wire RN

The moat

Streams ingredient cards, macro panels, swap suggestions natively. Visual-first rendering, no template.

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