Overview
Platform Purpose
The Village is a member-owned community platform providing sovereign data storage, AI-assisted features, and privacy-by-design architecture. Communities operate with full data ownership and governance-protected AI assistance.
Deployment Facts
- Duration: 11+ months in production
- Tenant Model: Single-tenant (multi-tenant planned)
- AI Features: 4 governed features live
- Services/Response: 6 governance checks
Architecture Mapping
Each Village AI feature maps to specific Tractatus governance services. The table below shows how the six services coordinate for each feature.
| Village Feature | Primary Service | Function |
|---|---|---|
| Home AI Responses | BoundaryEnforcer | Blocks values judgments, defers to human |
| User Query Processing | CrossReferenceValidator | Prevents prompt injection, validates intent |
| Session Management | ContextPressureMonitor | Tracks session health, triggers handoffs |
| Multi-Step Operations | MetacognitiveVerifier | Detects scope creep, requires review |
| Feature Flags | InstructionPersistenceClassifier | Persistence classification for settings |
| Consent Handling | PluralisticDeliberationOrchestrator | Multi-stakeholder decisions |
The Home AI Flow
When a user submits a query to Home AI, it passes through six verification stages before a response is generated. This flow operates in the critical execution path.
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1
User Query Received
User submits query via Help Chat widget or story assistance
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2
BoundaryEnforcer Check
Is this a values question requiring human judgment?
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3
CrossReferenceValidator Check
Does this conflict with stored instructions or attempt injection?
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4
ContextPressureMonitor Check
Is session health within acceptable bounds?
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5
Query Processing
RAG system retrieves context with permission filtering
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6
Response Generation
AI generates response (Claude Haiku for non-EN, local Llama for EN)
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7
MetacognitiveVerifier Check
Is response appropriate to query scope?
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8
Delivery
Response delivered to user with source attribution
Governed Features in Detail
RAG-Based Help Centre
Vector search over indexed help content, stories, and documentation. Results filtered by user permissions before inclusion in context.
Document OCR
Automated text extraction from uploaded documents. Operates under explicit consent controls with audit logging.
Story Assistance
AI-assisted writing suggestions for family stories. Content suggestions filtered through BoundaryEnforcer to prevent inappropriate recommendations.
AI Memory Transparency
User-controlled summarisation with full audit dashboard. Members can view, edit, and delete what AI "remembers" about them.
Honest Limitations
This case study documents preliminary evidence from a single implementation. We are transparent about the following limitations:
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Single Implementation: Village is one platform. Generalisability to other contexts is unknown.
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Self-Reported Metrics: No independent verification of logged data has been conducted.
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Operator-Developer Overlap: Framework developer also operates Village (conflict of interest).
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Limited Adversarial Testing: No formal red-team evaluation has been conducted.
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Voluntary Invocation: AI could theoretically bypass governance if not configured to use it.
What This Demonstrates
Evidence Supports
- • Architectural governance can operate in production without prohibitive overhead
- • Six-service coordination is technically feasible
- • Governance violations are detectable and auditable
- • The framework learns from failures (documented incident responses)
Evidence Does NOT Support
- • Framework effectiveness at scale (thousands of concurrent users)
- • Generalisability across different AI systems
- • Resistance to sophisticated adversarial attacks
- • Regulatory sufficiency (EU AI Act compliance untested)
Explore Further
See the Village platform in action, or dive deeper into the technical architecture.