Large Language Model (LLM)
A transformer-architecture neural network trained on very large text corpora to predict the next token in a sequence, producing fluent natural-language output across a wide range of tasks.
What Large Language Model (LLM) means in practice
A Large Language Model is a transformer-based neural network with anywhere from a few billion to a few hundred billion parameters, trained to predict the next token in a sequence. In production enterprise use the practical question is rarely "which LLM" but "which LLM at which size, served where, with what guardrails". For sovereign deployments MindMap typically serves Llama 3.3 70B or Qwen 2.5 72B for high-quality general workloads, and Llama 3.3 8B or Mistral 7B for high-throughput specialised workloads. Closed-source frontier models (GPT-4, Claude, Gemini) cannot be deployed on-prem and are therefore ruled out for regulated buyers who cannot send data to external APIs.
Related terms
Foundation model →
A model trained on a broad corpus that can be adapted (via prompting, fine-tuning, or retrieval) to many downstream tasks rather than being purpose-built for one.
Fine-tuning →
Adapting a pretrained model to a specific domain or task by continuing training on a smaller, curated dataset.
Sovereign AI →
An architecture where customer data never leaves the network perimeter, model weights run on customer-controlled hardware, inference logs stay in the customer's SIEM, and the entire stack can operate air-gapped.
More in this category
The Sovereign AI Playbook.
Enterprise generative AI that runs on your servers.
- 01Definition. The four non-negotiable properties of a sovereign deployment — and the three patterns that look sovereign but aren't.
- 02Why now. Three forces that converged in 2026: regulator pressure, the open-weights capability gap closing, and unit economics flipping.
- 03Reference architecture. The five-layer stack we deploy: applications → agent runtime → sovereign LLM → RAG + KB → data stores. With model and tooling choices for each.
- 04The regulators. SAMA · RBI · UK ICO · EU AI Act · DPDP · HIPAA — what each requires and how it maps to architecture.
All 62 terms, in plain language
Sovereign AI, RAG, agentic AI, IDP, MLOps and the regulations that shape enterprise AI.