Technical Overview
Building Sovereign AI Models
Learn how to build large language models embedding culture and language to drive economic and societal impact.
See What’s Included
Explore how to unlock economic opportunities, build tailored language models for country-specific needs, and create intelligence that will enable local impact. This technical brief covers all different aspects of training and fine-tuning sovereign AI models, including data curation, architecture selection, training methods, model evaluation, and production deployment.
Four Key Technical Pillars of Sovereign AI
Data and Benchmarks
High-quality local datasets and holistic benchmarks spanning accuracy, language, culture, history, geography, and law are key to training and customizing advanced AI models.
Models
Models can be built from scratch for full control or finetuned from high-quality commercially permissible open models, depending on the intended use and the quantity of locally curated data.
Hardware Infrastructure
All infrastructure, whether on‑premises or cloud-based, must be located within national borders and subject to robust governance and security to uphold data sovereignty.
Frameworks
Frameworks serve to unify all key pillars. Training frameworks enable model creation, while inference frameworks support deployment in real-world applications.