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+

Overview

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Platform Purpose

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+ 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. +

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Deployment Facts

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  • + Duration: + 11+ months in production +
    • +
  • + Tenant Model: + Single-tenant (multi-tenant planned) +
    • +
  • + AI Features: + 4 governed features live +
    • +
  • + Services/Response: + 6 governance checks +
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Architecture Mapping

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+ Each Village AI feature maps to specific Tractatus governance services. + The table below shows how the six services coordinate for each feature. +

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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Village FeaturePrimary ServiceFunction
Home AI ResponsesBoundaryEnforcerBlocks values judgments, defers to human
User Query ProcessingCrossReferenceValidatorPrevents prompt injection, validates intent
Session ManagementContextPressureMonitorTracks session health, triggers handoffs
Multi-Step OperationsMetacognitiveVerifierDetects scope creep, requires review
Feature FlagsInstructionPersistenceClassifierPersistence classification for settings
Consent HandlingPluralisticDeliberationOrchestratorMulti-stakeholder decisions
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The Home AI Flow

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+ 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. +
    1
    +
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    User Query Received

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    User submits query via Help Chat widget or story assistance

    +
    +
    2. +
  2. +
    2
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    BoundaryEnforcer Check

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    Is this a values question requiring human judgment?

    +
    +
    3. +
  3. +
    3
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    CrossReferenceValidator Check

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    Does this conflict with stored instructions or attempt injection?

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    4. +
  4. +
    4
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    ContextPressureMonitor Check

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    Is session health within acceptable bounds?

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    5. +
  5. +
    5
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    Query Processing

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    RAG system retrieves context with permission filtering

    +
    +
    6. +
  6. +
    6
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    Response Generation

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    AI generates response (Claude Haiku for non-EN, local Llama for EN)

    +
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    7. +
  7. +
    7
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    MetacognitiveVerifier Check

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    Is response appropriate to query scope?

    +
    +
    8. +
  8. +
    8
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    Delivery

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    Response delivered to user with source attribution

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    +
    9. +
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Governed Features in Detail

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RAG-Based Help Centre

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+ Vector search over indexed help content, stories, and documentation. + Results filtered by user permissions before inclusion in context. +

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+ Services: CrossReferenceValidator, BoundaryEnforcer +
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Document OCR

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+ Automated text extraction from uploaded documents. + Operates under explicit consent controls with audit logging. +

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+ Services: PluralisticDeliberationOrchestrator (consent) +
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Story Assistance

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+ AI-assisted writing suggestions for family stories. + Content suggestions filtered through BoundaryEnforcer to prevent + inappropriate recommendations. +

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+ Services: BoundaryEnforcer, MetacognitiveVerifier +
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AI Memory Transparency

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+ User-controlled summarisation with full audit dashboard. + Members can view, edit, and delete what AI "remembers" about them. +

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+ Services: InstructionPersistenceClassifier, PluralisticDeliberationOrchestrator +
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+

Honest Limitations

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+ This case study documents preliminary evidence from a single implementation. + We are transparent about the following limitations: +

+ +
    +
  • + + + +
    + Single Implementation: + Village is one platform. Generalisability to other contexts is unknown. +
    +
    • +
  • + + + +
    + Self-Reported Metrics: + No independent verification of logged data has been conducted. +
    +
    • +
  • + + + +
    + Operator-Developer Overlap: + Framework developer also operates Village (conflict of interest). +
    +
    • +
  • + + + +
    + 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. +
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What This Demonstrates

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Evidence Supports

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  • • 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)
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+

Evidence Does NOT Support

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  • • 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)
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+

Explore Further

+

+ See the Village platform in action, or dive deeper into the technical architecture. +

+
+ + Visit the Village → + + + System Architecture → + + + Research Details → + +
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+ +