Content-to-data transformation at institutional scale
Every production, course, and content library in the PG ecosystem is engineered to yield structured, rights-cleared, training-ready Arabic data.
The problem
AI systems are only as good as their training data — and high-quality Arabic media data is scarce, fragmented, and rarely rights-cleared. Dialect diversity compounds the challenge: Gulf, Levantine, Egyptian, and Modern Standard Arabic each require dedicated coverage that generic web scraping cannot provide.
Our approach
PG Holding builds data as a first-class output, not a by-product. Production pipelines at PG Studios embed structured metadata, annotation, and rights management from day one. PG Kids’ content library adds child-safe, education-aligned Arabic media. PG Academy generates instructional and process data. The result is a growing portfolio of Arabic media datasets designed for model training, fine-tuning, and evaluation.
What the data layer offers
- Rights-cleared Arabic audio, video, animation, and dialogue datasets
- Multi-dialect coverage with native-speaker quality control
- Structured annotation: transcripts, alignment, emotion, scene, and cultural metadata
- Licensing frameworks for AI labs, data centers, and research institutions
- Custom dataset development and evaluation partnerships
Who this is for
AI companies training or fine-tuning Arabic-capable models. Data centers and sovereign AI programs building national capability. Research institutions requiring culturally grounded Arabic corpora. Enterprises deploying Arabic-first AI products.