Data Labeling AI Agent
After behavioral signals are captured, the Data Labeling Agent transforms raw event data into structured, contextualized profiles. This includes sentiment tagging, intent classification, cohort analysis, and psychographic segmentation.
The labeling process leverages a hybrid active-learning loop that combines:
Rewarded Labeling Task + Snorkel: Programmatic annotation and weak supervision frameworks for efficient auto-labeling.
Reconfirm Correction: Re-using our Questionaries Specialist AI Agent that interacts with users to refine inferences.
Functional Design:
Agents cross-reference behavioral logs with inferred intents and yield profiles.
All annotations are stored in IPFS-based encrypted graphs for portability and composability.
This agent evolves in sophistication as it interacts with more users. It helps the JustFAB system identify which group users are "yield maximizers," "explorers," or "social influencers" with detail demand for any parties in need. For example, a toothbrush brand want to know interest of "Thailand male users with income around 5000 bath a month"
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