Data Distribution AI Agent
The final and most visible layer is the Data Distribution Agent. Its goal is to generate personalized recommendations, optimize airdrop routing, and strategically match users with tasks, mini-games, or campaigns that align with both user preferences and ecosystem incentives.
This is where raw and labeled data becomes tokenized utility:
Core Capabilities:
Game recommendation ranking models based on TensorFlow Recommenders
Airdrop prediction models (RL-trained using historical quest-to-airdrop conversion rates)
Contextual ad engines and native reward placement
Agent-driven segmentation for incentivized watch-to-earn or refer-to-earn mechanics
Technologies Used:
LangChain Framework: LLM-powered decision routing + game strategy generation
NVIDIA Merlin / TF Recommenders: High-performance, batch and real-time model serving
Microsoft Personalizer (optional API): Reinforcement learning-based user ranking
The output is deployed across user-facing channels like JustFAB game (Telegram, Line, Zalo, etc), JustFAB web portal, and embedded widgets in partner games. Recommendations are issued in natural language and adapted to local context (Web2.5 localization), ensuring low-friction UX and maximum impact.
Deployment Strategy
Each of the above AI agents operates independently but is coordinated through an agent orchestration layer. This layer is built using:
AutoGen frameworks
Custom backend with vector database support (e.g., Weaviate, Pinecone)
Modular, interoperable APIs with EVM hooks for reward execution
🔐 Privacy & Interoperability
All agent outputs are privacy-preserving by design:
No personally identifiable information (PII) is collected or stored.
Data labeling and recommendations happen on ephemeral sessions or ZK-enabled pseudonyms.
Data assets can be exported and tokenized as user-owned credentials as SFTs Data Token using ERC404 standard.
By combining best-in-class AI agent frameworks with decentralized, privacy-respecting infrastructure, JustFAB transforms gameplay into a frictionless, rewarding data economy—all while protecting the user at every step.
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