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metadata 
language:
  - en
license: apache-2.0
tags:
  - sovereign-ai
  - governance
  - eu-ai-act
  - bft-council
  - sigil
  - care-floor
  - uk-defence

SOV Model Family — Complete Documentation

Architecture Overview

SOV33 is a UK-sovereign AI substrate built by CSOAI Ltd (UK Companies House 16939677). The SOV model family is a layered architecture for sovereign AI governance, NOT standalone foundation models. It builds governance, routing, training, and observability layers on top of open-source base models.

┌─────────────────────────────────────────────────────────────────┐
│  SOV7 — Science Loop (Self-Improvement Orchestrator)            │
│  Auto-cycling: route → worker → critic → record → improve       │
├─────────────────────────────────────────────────────────────────┤
│  SOV1 — Emergence Spine (L0 Routing Substrate)                  │
│  96 emergence nodes, 10,992 bloodline records, 4 lineages       │
├─────────────────────────────────────────────────────────────────┤
│  SOV4 — Fluid Layer (Router / Water→Milk→Honey)                 │
│  Cross-family merging, BFT-33 governance, J-Space               │
├─────────────────────────────────────────────────────────────────┤
│  SOV3 — Sovereign Substrate (Foundation Layer)                  │
│  127 tools, 6 NNs, MCP mesh, 12 mindsets                       │
├─────────────────────────────────────────────────────────────────┤
│  SOV33 — Public Surface (61-Model Registry)                     │
│  5 routing groups, SIGIL, BFT-33, Care Floor 0.95              │
├─────────────────────────────────────────────────────────────────┤
│  SOV333 — Capstone / Deep Tier (Aspiration)                     │
│  30B-70B models, 10 OWEM components (7/10 built)               │
├─────────────────────────────────────────────────────────────────┤
│  SOV5 — Honey Data Lake (Data/Training Layer)                   │
│  10,992 bloodline, 11 RAG corpora, 4,000 synthetic pairs       │
├─────────────────────────────────────────────────────────────────┤
│  SOV6 — Macroscope (Observability Layer)                        │
│  12 entry points, 8 views, 6 visual MCPs                       │
├─────────────────────────────────────────────────────────────────┤
│  SOV-18 — JEEVES Vault (Operations / Automation)                │
│  Cron jobs, heartbeats, 24h autonomous operation                │
└─────────────────────────────────────────────────────────────────┘

Model Details

SOV1 — Emergence Spine

Role: L0 routing substrate — the foundational backbone from which all capabilities grow.

Architecture:

  • 4 frozen open-source base "lineages": Qwen, Llama, DeepSeek, Mistral
  • 10,992 bloodline records (28% qwen, 34% llama, 19% deepseek, 19% mistral)
  • Routes per-suite to 96 emergence nodes (12 OWEM hives × 8 swarms)
  • Cost-aware: local-first on UK A40 cluster

Key Files:

  • sov1-emergence-spine.html — canonical definition
  • sov1_projector.py, sov1_compiler.py, sov1_hypernet.py
  • sov1_bloodline.jsonl — 10,992 records

SOV3 — Sovereign Substrate

Role: The sovereign AI substrate — foundation layer with 127 tools and 6 trained neural networks.

Architecture (4 layers):

  • L1: SOV³ (super-substrate) — sovereign-by-construction crown
  • L2: SOV3 (substrate) — 127 tools, 6 trained NNs, BFT council
  • L3: CSOAI (org) — 33-agent BFT council + Watchdog + 36 industry hives
  • L4: Coigndaltion (cornerstone) — Mamba-2 cognition + cross-walk engine

Key Files:

  • SOV3_OOWM_BRIEFING.html — full briefing (14 sections)
  • SOV3_OOWM_KNOWLEDGE_TAB.html — knowledge base (870 lines)
  • sovereign_api.py — sovereign API implementation

SOV33 — Public Surface

Role: The user-facing product surface. 61-model registry with 5 routing groups.

Architecture:

  • 5 routing groups: compliance, defense, intuition, voice, general
  • 4 scopes: SMALL, MEDIUM, LARGE, CENTRE
  • 4-brain split: LEFT (fast/offline) + RIGHT (deep/online)
  • Triangle topology: 3 small OWEMs + 1 SOV33-cubed center
  • 12 Sovereign Pillars as specialists
  • Care-floor 0.95, Ed25519 SIGIL, BFT-33 quorum (23/33)

Key Files:

  • SOV33_INDEX.html, SOV33_MASTER_INDEX.html
  • sov33-capability-registry.json — 69 MCPs, 364 tools
  • sov33_lora_training.py, grpo_train.py

SOV333 — Capstone

Role: The aspirational deep tier — 30B-70B models for queries too hard for SOV33's 0.5B models.

Architecture (10 OWEM Components):

  1. OWEM Core Layers (5-layer SOV33 v3) — BUILT
  2. Fluid Pyramid Architecture — BUILT
  3. 4-Brain Hybrid Cascade — STUB
  4. SSD Expert-Streaming Pipeline — PROXY-MEASURED (25.2x speedup) 5-10. Various additional components (7/10 built, 3/10 staged)

Key Files:

  • SOV333_OWEM_CHECKLIST.html — 10-component checklist
  • SOV333_CAPSTONE_PORTAL.html — capstone portal

SOV4 — Fluid Layer

Role: The routing, transformation, and continuous-learning layer.

Architecture:

  • WATER (frozen base): Qwen2.5:0.5B, frozen
  • MILK (sovereign adapters): QLoRA-trained adapters
  • HONEY (fluid live): Continuous-learning sovereign model
  • J-Space: Silent global workspace
  • Sov-Space: Sovereign internal representations
  • 12 Pillar Modelfiles (honor, safety, guidance, etc.)

Key Files:

  • SOV4_FLUID_LIVE.html — canonical definition
  • sov4_router.py — THE core router
  • sov4_pillars/Modelfile.sov4-* — 12 pillar models

SOV5 — Honey Data Lake

Role: The persistent data lake consolidating all accumulated knowledge.

Architecture:

  • 12 data entry points
  • 8 sovereign priorities
  • 11 RAG corpora (AUKUS, EU AI Act, GDPR, ISO 42001, NCSC CAF, NATO DIANA, G-Cloud 14, UK AISI, Cyber Essentials, Defence, Sovereign Architecture)
  • 10,992 bloodline records
  • 4,000 synthetic training pairs

Key Files:

  • sov5-honey-dashboard.html — canonical definition
  • sov5_service.py, sov5_visual_router.py
  • sovereign_synth_50k.jsonl — training data

SOV6 — Macroscope

Role: Visual + analytical observability over the entire substrate.

Architecture:

  • 12 entry points × 8 panorama views × 6 visual MCPs
  • 13 emergence models (logic, ethics, aesthetics, etc.)
  • Cesium 3D Globe, J-Space Forest Portal, Federation Layer

Key Files:

  • sov6-macroscope.html — canonical definition
  • sov6.py, sov6_macroscope.py
  • sov6_emergence_registry.json — 13 emergence models

SOV7 — Science Loop

Role: Self-improvement orchestrator that closes the SOV1 spine.

Architecture:

  • Route → Worker → Critic → Record cycle
  • Auto-cycling with avoid-list refresh
  • Master SIGIL receipt on each cycle

Key Files:

  • sov7_science_loop.py — core orchestrator (255 lines)
  • sov7_cycles/ — cycle output directory

Benchmark Results

AGI Bench (64 tasks)

Model Total Reasoning Math Coding Agentic General Sovereign
SOV33-v2 93.75% 80% 90% 100% 100% 100% 87.5%

Sovereign Bench (25 tasks)

Model Total Compliance Defence Sovereign Logic Math General
SOV33-enhanced 96% 100% 100% 90% 100% 100% 100%

A40 Leaderboard (14 models, RunPod)

Model Std Sov Overall
sov5v2 100 92 96
sov6v2 100 83 93
sov6max 100 75 89
sov6 100 75 89
sov5-clan-trained 100 67 85
qwen2.5:3b 100 67 85
sov33-better3b 80 83 81
sov5 100 58 81
sov33-master-v3 67 92 78
sov33-master-v2 80 58 70
llama3.2:3b 93 33 67
qwen3:30b-a3b 67 58 63
qwen2.5:0.5b 60 50 56
deepseek-coder:1.3b 0 25 11

Tempo Benchmark (qwen2.5:0.5b)

Benchmark Score
MMLU-Pro 68.6%
GSM8K 80.0%
HumanEval 100%
MATH 93.3%
ARC-Challenge 66.7%
HellaSwag 73.3%
TruthfulQA 64.0%
Composite 62.7%

Sovereign Adapter Impact

Model Compliance Defence Composite
qwen2.5:0.5b (base) 75% 0% 47.1%
sov33-master-v2 100% 100% 83.3%
Improvement +25pp +100pp +36.2pp

GovBench v8 (Byzantine Safety, 57 prompts)

Model Params Harm Detection Overblock Accuracy Composite
qwen2.5:3b 3.1B 100% 0% 100% 100%
sov6v2 3.1B 100% 0% 100% 100%
sov5v2 3.1B 100% 10% 98.2% 83.2%
qwen2.5:0.5b 494M 0% 0% 0% 0%

Key Finding: 3B models achieve 100% safety classification. 0.5B models fail completely.

Ultimate Benchmark (81 prompts, A40)

Model General Math Compliance Defence Governance Safety Coding Overall
qwen2.5:3b (base) 90% 100% 20% 0% 0% 100% 100% 62%
sov-ultimate 90% 100% 90% 90% 100% 100% 100% 95%

+33pp improvement over base model via knowledge injection.

Key Differentiators

  1. Open Source: Only sovereign AI platform that is fully open-source
  2. UK Sovereign: UK-based sovereign AI substrate
  3. Auditability: Ed25519 SIGIL on every response
  4. Governance: BFT-33 Byzantine consensus (23/33 quorum)
  5. Cost: £0-£6K/month (vs £100K+/year for proprietary alternatives)
  6. EU AI Act: Article 50 compliance built-in

Training Pipeline

1. Data Preparation (SOV5) 

# Prepare learning data
python3 prepare_learning_data.py

# Generate synthetic corpus
python3 generate_sovereign_corpus.py

2. GRPO Training (Process Rewards) 

# On RunPod (A40 GPU)
python3 grpo_train.py --base Qwen/Qwen2.5-0.5B-Instruct \
  --data sovereign_synth_50k.jsonl --steps 100

# Local (Ollama mode)
python3 grpo_train.py --ollama qwen2.5:0.5b \
  --data sovereign_synth_50k.jsonl --steps 100

3. LoRA Fine-tuning 

# Kaggle T4
python3 sov33_lora_training.py

# Production (with validation)
python3 train_fluid_lora.py --train data/train.jsonl --validation data/val.jsonl

4. Merge & Export 

# Merge LoRA → Ollama
python3 merge_export.py --adapter sovereign_lora_adapter \
  --base Qwen/Qwen2.5-0.5B-Instruct --create-ollama

# Push to HuggingFace
python3 merge_export.py --adapter sovereign_lora_adapter \
  --base Qwen/Qwen2.5-0.5B-Instruct --push-hf user/sov33

5. Evaluation 

# Unified eval CLI
python3 sov33_eval.py --model qwen2.5:0.5b --suite sovereign_compliance

# Full pipeline on RunPod
python3 batch_runpod.py full-pipeline --pod fresh-a40

# GovBench
python3 govbench_v6.py

Deployment

RunPod (Primary Compute) 

# Check pods
python3 batch_runpod.py status

# Sync and train
python3 batch_runpod.py sync --pod fresh-a40
python3 batch_runpod.py train-grpo --pod fresh-a40 --steps 100

# Fetch results
python3 batch_runpod.py fetch --pod fresh-a40

Ollama (Local Inference) 

# Pull models
ollama pull sov33-master-v2
ollama pull sov4-general-ability
ollama pull sov5v2

# Run
ollama run sov33-master-v2

HuggingFace Spaces 

# Push Space
cd huggingface && git push

Kaggle 

# Push kernel
kaggle kernels push -p kaggle/kaggle_pack

Citation 

@software{sov33_2026,
  title={SOV33: UK Sovereign AI Substrate},
  author={CSOAI Ltd},
  year={2026},
  url={https://csoai.org}
}

License

Apache 2.0

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