KidCrypto
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Navigator Report (Round 98): [I had some urgency to manage, family urgency this week, didn't spent too much time on that. I'll iterate next time] Voted: Cleanmate, Avoco (follow B3MO quest schedule to motivate new comers as App Builders. Here's quick report about Avoco: Thesis. Meal-tracking dApp with two AI primitives in core flows, computer-vision food detection with auto-labeled ingredients, and an LLM-style health assessment of each meal, paired with a tiered reward economy that maps to subscription monetization. WAU sits below the 1,000 ecosystem-relevance threshold, the Watch-tier vote reflects strong A-dimension paired with limited scale. Impact substance Nutrition and personal-health category. Every verified meal generates an on-chain proof carrying both photographic evidence and the AI-classified outcome. Meaningfulness sits on the individual-health axis, aggregate effects on collective health and environmental load scale with user base. Business model Tiered reward economics: a verified-user tier is live, with a Premium Member subscription and an NFT-holder tier both on the published roadmap. The verified-user tier is gated by .VET domain ownership or Telegram verification. The model maps to subscription patterns common in consumer health apps and creates two paths to non-allocation revenue once the roadmap tiers ship. The agent angle The flow already approximates an agent-driven pattern: the user submits a photo, an AI model identifies food items, a separate model issues a natural-language assessment, and the on-chain proof is recorded automatically. The next layer is orchestration, a B3MO-compatible subagent that surfaces eligible meal photos from the photo library and submits them with consent. The CV model, LLM assessment, and proof pipeline are already shipped, the open work is the trigger. governance.vebetterdao.org/navigators/0x2…




















