**Technical Overview**

# Building Sovereign AI Models

Learn how to build large language models embedding culture and language to drive economic and societal impact.

[Download Now](https://nvdam.widen.net/s/zqhnctvvnb/sovereign-ai-technical-overview)

## 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.