Upload README.md with huggingface_hub

README.md

@@ -9,13 +9,17 @@ tags:
 - xgboost
 - sklearn
 - gcc
+- agentic-commerce
+- ocg-dubai
 library_name: sklearn
 pipeline_tag: tabular-regression
 ---
 
 # GCC Ramadan Retail Demand Forecasting Model
 
-An XGBoost Regressor model for predicting retail demand in GCC (Gulf Cooperation Council) countries based on Islamic calendar features.
+> Built by [OCG Dubai](https://ocg-dubai.ar) — Agentic Commerce for the GCC
+
+An XGBoost Regressor model for predicting retail demand in GCC (Gulf Cooperation Council) countries based on Islamic calendar features. Part of the [OCG Dubai Agentic Commerce](https://ocg-dubai.ar) platform, which uses AI agents to power intelligent retail operations across the Gulf region.
 
 ## Model Description
 
@@ -127,6 +131,13 @@ The model was trained on a synthetic dataset representing 15+ years of retail de
 - `config.json` - Model configuration and metadata
 - `feature_importances.json` - Feature importance scores
 
+## About OCG Dubai
+
+[OCG Dubai](https://ocg-dubai.ar) is an AI-powered Agentic Commerce platform built for the GCC market. We use multi-agent systems to automate retail intelligence, demand forecasting, halal compliance, and dynamic pricing — all calibrated for Islamic calendar seasonality and regional consumer behavior.
+
+- Website: [ocg-dubai.ar](https://ocg-dubai.ar)
+- Dataset: [GencoDiv/gcc-ramadan-retail-patterns](https://huggingface.co/datasets/GencoDiv/gcc-ramadan-retail-patterns)
+
 ## License
 
 MIT License