diff --git a/docs/business-intelligence/governance-bi-tools.docx b/docs/business-intelligence/governance-bi-tools.docx
new file mode 100644
index 00000000..6bd815fa
Binary files /dev/null and b/docs/business-intelligence/governance-bi-tools.docx differ
diff --git a/docs/business-intelligence/governance-bi-tools.md b/docs/business-intelligence/governance-bi-tools.md
new file mode 100644
index 00000000..9add8e88
--- /dev/null
+++ b/docs/business-intelligence/governance-bi-tools.md
@@ -0,0 +1,672 @@
+---
+title: "Governance Business Intelligence Tools: Research Prototype"
+version: "1.0.0"
+date: "2025-10-27"
+status: "Research Prototype"
+authors: "John Stroh (with Claude Code AI assistance)"
+document_type: "Research Documentation"
+confidential: false
+license: "Apache 2.0"
+
+version_history:
+  - version: "1.0.0"
+    date: "2025-10-27"
+    changes:
+      - "Initial documentation of BI tools prototype"
+      - "Current capability assessment"
+      - "Short-term and long-term development roadmap"
+      - "Research goals and limitations documented"
+
+media_rollout_notes: |
+  IMPORTANT: This is a research prototype demonstrating governance ROI visualization concepts.
+  Before public announcement:
+  - Validate cost calculation methodology with industry data
+  - Add disclaimers about illustrative values
+  - Test with pilot organizations for feedback
+  - Consider peer review of approach
+
+  Timeline considerations:
+  - Blog post planned for early November 2025
+  - UI integration requires careful messaging about prototype status
+  - Media rollout should emphasize research contribution, not commercial tool
+
+strategic_assessment: |
+  CRITICAL INSIGHT: ROI visualization may be the key differentiator for framework adoption.
+  Organizations don't buy "governance frameworks" - they buy incident cost avoidance,
+  compliance evidence, and team productivity metrics. This tool demonstrates how
+  AI governance can be measured and justified to leadership.
+
+  However: Must maintain research integrity. Current cost factors are illustrative
+  placeholders, not validated industry benchmarks.
+---
+
+# Governance Business Intelligence Tools
+## Research Prototype for AI Safety Framework ROI Visualization
+
+**Version**: 1.0.0 (Research Prototype)
+**Date**: October 27, 2025
+**Status**: Proof-of-Concept / Active Research
+
+---
+
+## Executive Summary
+
+This document describes a novel approach to **quantifying AI governance framework value** through business intelligence tools. The Tractatus Framework has implemented a research prototype that transforms technical governance metrics into executive-decision-relevant insights including cost avoidance, compliance evidence, and team productivity analysis.
+
+**Key Innovation**: Automatic classification of AI-assisted work by activity type, risk level, and stakeholder impact enables real-time ROI calculation and organizational benchmarking.
+
+**Research Status**: Current implementation demonstrates feasibility. Cost factors are illustrative placeholders requiring validation. Methodology is sound; specific values need organizational customization.
+
+**Strategic Potential**: Early evidence suggests ROI visualization is the critical missing piece for governance framework adoption at scale.
+
+---
+
+## 1. Current Capability (v1.0 Prototype)
+
+### 1.1 Activity Classification System
+
+The framework automatically classifies every governance decision by:
+
+- **Activity Type**: Client Communication, Code Generation, Documentation, Deployment, Compliance Review, Data Management
+- **Risk Level**: Minimal → Low → Medium → High → Critical
+- **Stakeholder Impact**: Individual → Team → Organization → Client → Public
+- **Data Sensitivity**: Public → Internal → Confidential → Restricted
+- **Reversibility**: Easy → Moderate → Difficult
+
+**Implementation**: `activity-classifier.util.js` applies deterministic rules based on file paths, action metadata, and service patterns.
+
+**Accuracy**: Classification logic is heuristic-based. Requires validation with real organizational data.
+
+### 1.2 Cost Avoidance Calculator (Illustrative)
+
+**Purpose**: Demonstrates *potential* for quantifying governance value in financial terms.
+
+**Current Implementation**:
+- Default cost factors (ILLUSTRATIVE, not validated):
+  - CRITICAL: $50,000 (avg security incident cost)
+  - HIGH: $10,000 (client-facing error)
+  - MEDIUM: $2,000 (hotfix deployment)
+  - LOW: $500 (developer time)
+
+**User Configuration**: Organizations can input their own cost models via API endpoints.
+
+**Calculation Method**:
+```
+Cost Avoided = Σ (Blocked Violations × Severity Cost Factor)
+```
+
+**IMPORTANT LIMITATION**: Current factors are research placeholders. Each organization must determine appropriate values based on:
+- Historical incident costs
+- Industry benchmarks (e.g., Ponemon Institute data)
+- Insurance claims data
+- Regulatory fine schedules
+- Internal accounting practices
+
+**Research Question**: Can governance ROI be meaningfully quantified? Prototype suggests yes, but methodology requires peer validation.
+
+### 1.3 Framework Maturity Score (0-100)
+
+**Concept**: Measure organizational "governance maturity" based on framework usage patterns.
+
+**Components** (Equal Weight):
+1. **Block Rate Score**: Lower block rate = better (framework teaching good practices)
+2. **AI Adoption Score**: Higher AI-assisted work = better (leveraging automation)
+3. **Severity Score**: Fewer critical violations = better (reducing high-impact risks)
+
+**Formula**:
+```
+Maturity = (BlockRateScore + AIAdoptionScore + SeverityScore) / 3
+
+Where:
+  BlockRateScore = max(0, 100 - (blockRate × 1000))
+  AIAdoptionScore = (aiDecisions / totalDecisions) × 100
+  SeverityScore = max(0, 100 - (criticalCount / total × 1000))
+```
+
+**Interpretation**:
+- 80-100: Excellent (framework teaching good practices)
+- 60-79: Good (team adapting to governance)
+- 0-59: Learning (framework actively preventing violations)
+
+**Research Status**: Algorithm is preliminary. Requires longitudinal studies to validate correlation between score and actual governance outcomes.
+
+### 1.4 Team Performance Comparison (AI vs Human)
+
+**Hypothesis**: AI-assisted work may have different governance risk profiles than direct human operations.
+
+**Classification**:
+- **AI Assistant**: Actions by FileEditHook, BoundaryEnforcer, ContextPressureMonitor, MetacognitiveVerifier
+- **Human Direct**: Manual database operations, configuration changes, direct file writes
+
+**Metrics Tracked**:
+- Total decisions per category
+- Block rate (violations prevented / total actions)
+- Violation severity distribution
+
+**Research Question**: Does AI assistance improve governance compliance? Early data suggests potential, but sample size insufficient for conclusions.
+
+### 1.5 Activity Type Analysis
+
+**Demonstrates**: Governance impact varies by work type.
+
+**Example Output** (From Current Prototype):
+- Client Communication: 100% block rate (1/1 - prevents public errors)
+- Code Generation: 50% block rate (1/2 - some errors caught)
+- Documentation: 33% block rate (1/3)
+- Autonomous Processing: 0% block rate (46/46 - clean performance)
+
+**Value for Leadership**: "Framework prevents 100% of client-facing violations" is more compelling than "3 blocks this week."
+
+### 1.6 Scaling Projections (Enterprise Deployment)
+
+**Purpose**: Answer "What if we deploy to 70,000 users?"
+
+**Method**: Linear extrapolation from current data
+```
+ProjectedBlocks(Users) = CurrentBlockRate × EstimatedDecisionsPerUser × UserCount
+```
+
+**Example Output**:
+- 1,000 users: ~30 violations prevented/month
+- 10,000 users: ~300 violations prevented/month
+- 70,000 users: ~2,100 violations prevented/month
+
+**CRITICAL DISCLAIMER**:
+- Assumes linear scaling (likely incorrect)
+- Assumes homogeneous user populations (unrealistic)
+- Does not account for learning curves, cultural differences, varying use cases
+- **For illustrative purposes only**
+
+**Research Need**: Actual deployment studies required to validate scaling assumptions.
+
+---
+
+## 2. Short-Term Development (3-6 Months)
+
+### 2.1 Cost Model Validation
+
+**Goal**: Replace placeholder values with industry-validated benchmarks.
+
+**Approach**:
+1. Literature review (Ponemon Institute, SANS, IBM Cost of Data Breach reports)
+2. Survey pilot organizations for actual incident costs
+3. Develop cost calculation methodology paper for peer review
+4. Create cost model templates for different industries (Healthcare/HIPAA, Finance/PCI-DSS, SaaS/SOC2)
+
+**Deliverable**: Whitepaper on "Quantifying AI Governance ROI: A Methodological Framework"
+
+### 2.2 Interactive Cost Configuration UI
+
+**Goal**: Allow organizations to customize cost factors without code changes.
+
+**Features**:
+- Modal dialog for editing cost factors by severity
+- Text fields for rationale (audit trail)
+- Industry template selection (Healthcare, Finance, SaaS)
+- Import/export cost models (JSON)
+- Approval workflow for cost model changes
+
+**Technical**: Frontend modal + API endpoints already implemented, UI needs completion.
+
+### 2.3 Compliance Mapping
+
+**Goal**: Map governance rules to actual regulatory requirements.
+
+**Example**:
+```
+inst_072 (Credential Protection) satisfies:
+  - SOC2 CC6.1 (Logical and physical access controls)
+  - GDPR Article 32 (Security of processing)
+  - ISO 27001 A.9.4.3 (Access credential controls)
+```
+
+**Value**: Transform "governance tool" into "compliance evidence generator."
+
+**Implementation**:
+- Add `complianceReferences` field to instruction schema
+- Create compliance report generator (PDF export)
+- Dashboard section showing "X regulations satisfied by Y blocks"
+
+### 2.4 Trend Analysis & Learning Curves
+
+**Goal**: Show governance improvement over time.
+
+**Metrics**:
+- 7-day, 30-day, 90-day block rate trends
+- Time-to-clean (days until 90% compliance rate)
+- Recidivism tracking (same violation repeated)
+- Rule effectiveness (block rate vs false positive rate)
+
+**Visualization**: Line charts, trend indicators, "days since last critical violation"
+
+### 2.5 False Positive Tracking
+
+**Goal**: Distinguish between "good blocks" and "framework too strict."
+
+**Features**:
+- "Override" button on blocks (with required justification)
+- Track override rate by rule
+- Flag rules with >15% override rate for review
+- Feedback loop: High override rate → rule tuning recommendation
+
+**Value**: Demonstrates framework learns and adapts, not just enforces blindly.
+
+---
+
+## 3. Long-Term Research Goals (6-18 Months)
+
+### 3.1 Tiered Pattern Recognition
+
+**Goal**: Detect governance risks before violations occur.
+
+**Tier 1 - Session Patterns** (6 months):
+- "Client communication editing sessions have 5× higher block rate"
+- "Deployment sessions Friday 5pm have 10× risk multiplier"
+- Alert: "Unusual activity pattern detected"
+
+**Tier 2 - Sequential Patterns** (12 months):
+- "After editing footer.js, 80% of sessions attempt credential changes next"
+- "Editing 3+ files in public/ folder predicts CSP violation"
+- Proactive warning: "This action sequence is high-risk"
+
+**Tier 3 - Temporal Anomalies** (18 months):
+- "5 GitHub URL changes in 1 hour (normal: 0.2/hour) - investigate"
+- "Credential file access outside work hours - alert security team"
+- Machine learning model for anomaly detection
+
+**Research Challenge**: Requires significant data volume. May need federated learning across organizations.
+
+### 3.2 Feedback Loop Analysis
+
+**Goal**: Measure framework's teaching effectiveness.
+
+**Metrics**:
+- **Learning Rate**: Block rate decrease over time = framework teaching good practices
+- **Recidivism**: Same violation type recurring = need training intervention
+- **Rule Effectiveness**: Optimal rule has high block rate + low false positive rate
+
+**Research Question**: Can governance frameworks actively improve team behavior vs just blocking violations?
+
+**Longitudinal Study Needed**: Track teams over 6-12 months, measure behavior change.
+
+### 3.3 Organizational Benchmarking
+
+**Goal**: "Your critical block rate: 0.05% (Industry avg: 0.15%)"
+
+**Requirements**:
+- Anonymized cross-organization data sharing
+- Privacy-preserving aggregation (differential privacy)
+- Standardized metrics for comparison
+- Opt-in consortium of organizations
+
+**Value**: Organizations can benchmark maturity against peers.
+
+**Challenges**:
+- Privacy concerns (competitive intel)
+- Definitional differences (what counts as "CRITICAL"?)
+- Selection bias (only high-maturity orgs participate)
+
+### 3.4 Multi-Factorial Cost Estimator (Advanced Tool)
+
+**Goal**: Move beyond simple severity multipliers to sophisticated cost modeling.
+
+**Factors**:
+- Severity level
+- Stakeholder impact (public vs internal)
+- Data sensitivity (PII vs public)
+- Reversibility (permanent vs easily fixed)
+- Regulatory context (GDPR fine schedules)
+- Time of discovery (pre-deployment vs post-incident)
+
+**Example**:
+```
+Cost = BaseCost(Severity) ×
+       ImpactMultiplier(Stakeholders) ×
+       SensitivityMultiplier(Data) ×
+       ReversibilityMultiplier ×
+       RegulatoryMultiplier
+```
+
+**Research Partnership**: Work with insurance companies, legal firms, incident response teams for validated cost models.
+
+### 3.5 Predictive Governance (Machine Learning)
+
+**Goal**: Predict which actions are likely to violate governance before execution.
+
+**Approach**:
+- Train ML model on historical decisions + outcomes
+- Features: file path, action type, time of day, session context, recent history
+- Output: Violation probability + recommended alternative
+
+**Example**: "80% chance this edit violates CSP. Suggest: use CSS class instead of inline style."
+
+**Research Challenge**: Requires large training dataset. May need synthetic data generation or federated learning.
+
+---
+
+## 4. Research Limitations & Disclaimers
+
+### 4.1 Current Prototype Limitations
+
+1. **Cost Factors Are Illustrative**: Default values ($50k for CRITICAL, etc.) are not validated. Organizations must supply their own values.
+
+2. **Small Sample Size**: Current data from single development project. Patterns may not generalize.
+
+3. **Classification Heuristics**: Activity type detection uses simple rules (file path patterns). May misclassify edge cases.
+
+4. **Linear Scaling Assumptions**: ROI projections assume linear scaling. Real deployments likely non-linear.
+
+5. **No Statistical Validation**: Maturity score formula is preliminary. Requires empirical validation against actual governance outcomes.
+
+6. **AI vs Human Detection**: Simple heuristic (service name). May incorrectly categorize some actions.
+
+### 4.2 Generalizability Concerns
+
+- Developed for web application development context
+- May not apply to: embedded systems, data science workflows, infrastructure automation, etc.
+- Cultural context: Developed in Western organizational structure; may not fit all governance cultures
+
+### 4.3 Ethical Considerations
+
+- Cost avoidance metrics could incentivize "blocking for metrics" rather than genuine risk reduction
+- Team comparison metrics risk creating adversarial AI vs Human dynamics
+- Benchmarking could pressure organizations to game metrics rather than improve governance
+
+**Mitigation**: Emphasize these tools inform decisions, not replace judgment. Framework designed for transparency and accountability, not surveillance.
+
+---
+
+## 5. Implementation Package (Trial Deployment)
+
+### 5.1 Deployment Components
+
+**For Organizations Piloting BI Tools**:
+
+1. **Dashboard Access** (`/admin/audit-analytics.html`)
+   - Summary metrics (Total Actions, Allowed, Blocked, Violations)
+   - Cost Avoidance Calculator (with custom cost model)
+   - Framework Maturity Score
+   - Team Performance Comparison
+   - Activity Type Analysis
+   - Enterprise Scaling Projections
+   - Future Research Roadmap
+
+2. **API Endpoints**:
+   - `GET /api/admin/audit-logs` - Raw audit data
+   - `GET /api/admin/audit-analytics` - Computed metrics
+   - `GET /api/admin/cost-config` - Current cost factors
+   - `POST /api/admin/cost-config` - Update cost model
+
+3. **Activity Classifier** (`src/utils/activity-classifier.util.js`)
+   - Automatic governance decision classification
+   - Business impact scoring (0-100 points)
+
+4. **Enhanced Hook Validators**:
+   - `validate-file-edit.js` - Logs activity context to MongoDB
+   - Captures: activity type, risk level, stakeholder impact, business impact
+
+### 5.2 Trial Deployment Checklist
+
+**Pre-Deployment**:
+- [ ] Organization defines custom cost factors (with rationale documentation)
+- [ ] Legal review of compliance mapping claims
+- [ ] Privacy assessment of data collection (especially team comparison metrics)
+- [ ] Training materials for interpreting BI metrics
+
+**During Trial** (Recommended: 30-90 days):
+- [ ] Weekly metric reviews with stakeholders
+- [ ] Collect feedback on cost model accuracy
+- [ ] Document false positive cases (override tracking)
+- [ ] Measure actual vs predicted ROI
+
+**Post-Trial**:
+- [ ] Validation report comparing predicted vs actual cost avoidance
+- [ ] User experience feedback (dashboard usability, metric relevance)
+- [ ] Recommendations for framework improvements
+- [ ] Publishable case study (with anonymization)
+
+### 5.3 Customization Guide
+
+**Cost Factor Configuration**:
+```json
+{
+  "CRITICAL": {
+    "amount": 50000,
+    "currency": "USD",
+    "rationale": "Average cost of data breach per Ponemon Institute 2024 report"
+  },
+  "HIGH": {
+    "amount": 10000,
+    "currency": "USD",
+    "rationale": "Estimated customer churn impact from public error"
+  }
+}
+```
+
+**Activity Classification Overrides**:
+Organizations may need to customize file path patterns for their codebase structure.
+
+Example: If client-facing code is in `app/client/` instead of `public/`:
+```javascript
+// In activity-classifier.util.js
+if (filePath.includes('app/client/') && !filePath.includes('admin/')) {
+  activityType = ACTIVITY_TYPES.CLIENT_COMMUNICATION;
+  // ...
+}
+```
+
+---
+
+## 6. Strategic Assessment
+
+### 6.1 Market Differentiation
+
+**Hypothesis**: AI governance frameworks fail adoption because value is intangible.
+
+**Evidence**:
+- Technical teams: "This is good governance" ✓
+- Executives: "What's the ROI?" ✗
+
+**Innovation**: This BI toolset provides the missing ROI quantification layer.
+
+**Competitive Landscape**:
+- Existing tools: Focus on technical compliance (code linters, security scanners)
+- Gap: No tools quantify governance value in business terms
+- Opportunity: First-mover advantage in "governance ROI analytics"
+
+### 6.2 Adoption Barriers
+
+**Technical**:
+- Requires MongoDB for audit logging
+- Needs integration with existing CI/CD pipelines
+- Custom classification rules for different codebases
+
+**Organizational**:
+- Requires leadership buy-in for cost model definition
+- Cultural resistance to "surveillance metrics" (team comparison)
+- Need for governance champion to interpret metrics
+
+**Validation**:
+- Current lack of peer-reviewed methodology
+- No industry benchmarks to compare against
+- Uncertain accuracy of cost calculations
+
+### 6.3 Research Publication Potential
+
+**Potential Papers**:
+
+1. **"Quantifying AI Governance ROI: A Classification-Based Approach"**
+   - Venue: ACM FAccT, AIES
+   - Contribution: Activity classification methodology
+   - Status: Prototype ready for pilot studies
+
+2. **"Framework Maturity Metrics for AI Safety Governance"**
+   - Venue: IEEE Software, Journal of Systems and Software
+   - Contribution: Maturity scoring algorithm validation
+   - Status: Needs longitudinal data
+
+3. **"Business Intelligence for AI Governance: Bridging Technical and Executive Perspectives"**
+   - Venue: Harvard Business Review, Sloan Management Review
+   - Contribution: Practitioner-oriented case studies
+   - Status: Needs trial deployments
+
+### 6.4 Commercialization Pathway (If Validated)
+
+**Potential Business Models** (Post-Research Validation):
+
+1. **Open-Source Core + Commercial Dashboard**
+   - Framework: Apache 2.0 (open)
+   - BI Dashboard: Commercial license with support
+
+2. **Managed Service (SaaS)**
+   - Host framework + BI tools
+   - Subscription pricing per user/month
+
+3. **Consulting & Customization**
+   - Framework implementation services
+   - Custom cost model development
+   - Organizational benchmarking studies
+
+**Prerequisites for Commercialization**:
+- Peer-reviewed validation of methodology
+- 5+ successful pilot deployments
+- Legal review of claims (avoid overpromising ROI)
+- Insurance/indemnification for cost calculation errors
+
+---
+
+## 7. Next Steps & Timeline
+
+### Immediate (November 2025)
+
+- [ ] **Validate cost calculation methodology** (literature review)
+- [ ] **Add disclaimers to dashboard** (illustrative values)
+- [ ] **Create blog post draft** (scheduled calendar entry)
+- [ ] **Update UI pages** with measured BI tool descriptions
+- [ ] **Peer review request** (academic governance researchers)
+
+### Short-Term (December 2025 - February 2026)
+
+- [ ] **Complete cost configuration UI** (modal dialog)
+- [ ] **Pilot deployment #1** (volunteer organization)
+- [ ] **Collect validation data** (actual vs predicted costs)
+- [ ] **Compliance mapping** (SOC2, GDPR, ISO 27001)
+- [ ] **False positive tracking** implementation
+
+### Medium-Term (March - August 2026)
+
+- [ ] **Tier 1 pattern recognition** (session patterns)
+- [ ] **Trend analysis dashboard** (7/30/90-day charts)
+- [ ] **Pilot deployment #2-3** (expand trial)
+- [ ] **First research paper submission** (methodology validation)
+- [ ] **Industry benchmark consortium** (recruit founding members)
+
+### Long-Term (September 2026 - March 2027)
+
+- [ ] **Tier 2 pattern recognition** (sequential patterns)
+- [ ] **Feedback loop analysis** (learning rate measurement)
+- [ ] **Organizational benchmarking beta** (5+ organizations)
+- [ ] **Case study publications** (anonymized trials)
+- [ ] **Commercial pilot consideration** (if research validates)
+
+---
+
+## 8. Conclusion
+
+The Governance Business Intelligence tools represent a **novel approach to quantifying AI governance value**. The current prototype successfully demonstrates feasibility of:
+
+1. Automatic activity classification for governance risk assessment
+2. Cost-based ROI calculation (methodology sound, values need validation)
+3. Framework maturity scoring (algorithm preliminary, needs empirical validation)
+4. Team performance comparison (AI vs Human governance profiles)
+5. Enterprise scaling projections (illustrative, assumes linear scaling)
+
+**Critical Success Factor**: Maintaining research integrity while demonstrating practical value.
+
+**Strategic Potential**: If validated through rigorous trials, these tools could become the critical missing piece for AI governance framework adoption at organizational scale.
+
+**Next Milestone**: Pilot deployment with cost model validation against actual incident data.
+
+---
+
+## Appendix A: Technical Architecture
+
+**Activity Classification Pipeline**:
+```
+File Edit Action
+  ↓
+Hook Validator (validate-file-edit.js)
+  ↓
+Activity Classifier (activity-classifier.util.js)
+  → Classifies: Type, Risk, Impact, Sensitivity
+  ↓
+Business Impact Calculator
+  → Calculates: 0-100 score
+  ↓
+MongoDB Audit Log
+  → Stores: Classification + Impact + Violations
+  ↓
+Analytics Controller (audit.controller.js)
+  → Aggregates: Cost avoided, Maturity score, Team comparison
+  ↓
+Dashboard UI (audit-analytics.html)
+  → Displays: ROI metrics for executives
+```
+
+**Data Model**:
+```javascript
+AuditLogEntry {
+  action: String,              // "file_edit_hook"
+  allowed: Boolean,            // true/false
+  violations: [Violation],     // Rule violations detected
+  activityType: String,        // "Client Communication"
+  riskLevel: String,           // "high"
+  stakeholderImpact: String,   // "public"
+  dataSensitivity: String,     // "public"
+  reversibility: String,       // "difficult"
+  businessImpact: Number,      // 0-100 score
+  timestamp: Date
+}
+```
+
+---
+
+## Appendix B: Cost Model Templates
+
+### Healthcare / HIPAA Template
+```json
+{
+  "CRITICAL": {
+    "amount": 100000,
+    "rationale": "PHI breach: $6.5M avg ÷ 65 incidents (Ponemon) = $100k/incident"
+  },
+  "HIGH": {
+    "amount": 25000,
+    "rationale": "HIPAA violation potential: OCR fine + remediation"
+  }
+}
+```
+
+### SaaS / SOC2 Template
+```json
+{
+  "CRITICAL": {
+    "amount": 50000,
+    "rationale": "Security incident: Customer churn + PR damage"
+  },
+  "HIGH": {
+    "amount": 10000,
+    "rationale": "SOC2 control failure: Audit remediation cost"
+  }
+}
+```
+
+---
+
+**Document Status**: Living document, updated regularly as research progresses.
+
+**Feedback**: hello@agenticgovernance.digital
+
+**Repository**: https://github.com/AgenticGovernance/tractatus-framework
+
+**License**: Apache 2.0
diff --git a/docs/business-intelligence/governance-bi-tools.pdf b/docs/business-intelligence/governance-bi-tools.pdf
new file mode 100644
index 00000000..d5abb0ae
Binary files /dev/null and b/docs/business-intelligence/governance-bi-tools.pdf differ
diff --git a/public/admin/dashboard.html b/public/admin/dashboard.html
index 1545666f..81ede35e 100644
--- a/public/admin/dashboard.html
+++ b/public/admin/dashboard.html
@@ -106,6 +106,49 @@
         </div>
       </div>
 
+      <!-- Business Intelligence Feature Card -->
+      <div class="bg-gradient-to-r from-purple-50 to-blue-50 rounded-lg shadow-sm border-2 border-purple-200 p-6 mb-8">
+        <div class="flex items-start justify-between">
+          <div class="flex-1">
+            <div class="flex items-center mb-2">
+              <svg class="h-6 w-6 text-purple-600 mr-2" fill="none" stroke="currentColor" viewBox="0 0 24 24">
+                <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 19v-6a2 2 0 00-2-2H5a2 2 0 00-2 2v6a2 2 0 002 2h2a2 2 0 002-2zm0 0V9a2 2 0 012-2h2a2 2 0 012 2v10m-6 0a2 2 0 002 2h2a2 2 0 002-2m0 0V5a2 2 0 012-2h2a2 2 0 012 2v14a2 2 0 01-2 2h-2a2 2 0 01-2-2z"/>
+              </svg>
+              <h3 class="text-lg font-bold text-gray-900">Business Intelligence Tools</h3>
+              <span class="ml-2 px-2 py-1 text-xs font-medium bg-purple-100 text-purple-800 rounded-full">Research Prototype</span>
+            </div>
+            <p class="text-sm text-gray-700 mb-3">
+              Transform governance logs into executive insights. Track cost avoidance, framework maturity, and team performance with real-time analytics.
+            </p>
+            <div class="grid grid-cols-1 md:grid-cols-3 gap-3 mb-4">
+              <div class="bg-white rounded p-3 border border-purple-100">
+                <p class="text-xs font-medium text-gray-500">Cost Avoidance</p>
+                <p class="text-sm text-gray-900">Track financial value of violations prevented</p>
+              </div>
+              <div class="bg-white rounded p-3 border border-purple-100">
+                <p class="text-xs font-medium text-gray-500">Maturity Score</p>
+                <p class="text-sm text-gray-900">Measure organizational governance learning</p>
+              </div>
+              <div class="bg-white rounded p-3 border border-purple-100">
+                <p class="text-xs font-medium text-gray-500">Team Performance</p>
+                <p class="text-sm text-gray-900">Compare AI-assisted vs human-direct work</p>
+              </div>
+            </div>
+            <div class="flex items-center space-x-3">
+              <a href="/admin/audit-analytics.html" class="inline-flex items-center px-4 py-2 bg-purple-600 text-white text-sm font-medium rounded-md hover:bg-purple-700">
+                View Analytics Dashboard
+                <svg class="ml-2 h-4 w-4" fill="none" stroke="currentColor" viewBox="0 0 24 24">
+                  <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M13 7l5 5m0 0l-5 5m5-5H6"/>
+                </svg>
+              </a>
+              <a href="/docs/business-intelligence/governance-bi-tools.pdf" class="text-sm text-purple-600 hover:text-purple-800 font-medium">
+                Read Documentation →
+              </a>
+            </div>
+          </div>
+        </div>
+      </div>
+
       <!-- Recent Activity -->
       <div class="bg-white rounded-lg shadow">
         <div class="px-6 py-4 border-b border-gray-200">
diff --git a/public/implementer.html b/public/implementer.html
index d0d4380f..5edea243 100644
--- a/public/implementer.html
+++ b/public/implementer.html
@@ -1108,6 +1108,31 @@ const govResponse = await fetch(
           </div>
         </div>
 
+        <!-- Business Intelligence Tools -->
+        <div class="bg-gradient-to-r from-purple-50 to-blue-50 rounded-lg p-6 shadow-md border-2 border-purple-200">
+          <div class="flex items-start mb-3">
+            <span class="text-3xl mr-3">📊</span>
+            <div class="flex-1">
+              <div class="flex items-center">
+                <h4 class="text-lg font-bold text-gray-900">Business Intelligence Tools</h4>
+                <span class="ml-2 px-2 py-1 text-xs font-medium bg-green-100 text-green-800 rounded-full">v1.0 Prototype Live</span>
+              </div>
+              <p class="text-sm text-gray-500">Status: Research Validation Phase</p>
+            </div>
+          </div>
+          <p class="text-sm text-gray-700 mb-3">
+            Transform governance logs into executive insights: cost avoidance calculator, framework maturity scoring, and team performance analytics. Demonstrates ROI of governance decisions in real-time.
+          </p>
+          <div class="text-xs text-gray-600 mb-3">
+            <strong>Current Features:</strong> User-configurable cost factors, maturity scoring (0-100), AI vs human performance comparison, enterprise scaling projections
+          </div>
+          <div class="flex items-center space-x-2">
+            <a href="/admin/audit-analytics.html" class="text-xs font-medium text-purple-600 hover:text-purple-800">View Dashboard →</a>
+            <span class="text-gray-300">|</span>
+            <a href="/docs/business-intelligence/governance-bi-tools.pdf" class="text-xs font-medium text-purple-600 hover:text-purple-800">Read Docs (PDF)</a>
+          </div>
+        </div>
+
         <!-- Framework Integrations -->
         <div class="bg-white rounded-lg p-6 shadow-md">
           <div class="flex items-start mb-3">
diff --git a/public/researcher.html b/public/researcher.html
index b5bc1188..b20adfe0 100644
--- a/public/researcher.html
+++ b/public/researcher.html
@@ -490,6 +490,17 @@
             <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M13 7h8m0 0v8m0-8l-8 8-4-4-6 6"/>
           </svg>
         </a>
+
+        <a href="/docs/business-intelligence/governance-bi-tools.pdf" target="_blank" class="flex items-center justify-between p-4 border-2 border-purple-200 bg-gradient-to-r from-purple-50 to-blue-50 rounded hover:border-purple-400 transition">
+          <div>
+            <span class="font-medium text-gray-900">Business Intelligence Tools: Measuring Governance ROI</span>
+            <span class="ml-2 text-xs bg-purple-100 text-purple-800 px-2 py-1 rounded">v1.0 Prototype</span>
+            <p class="text-xs text-gray-600 mt-1">Cost avoidance, maturity scoring, and team performance analytics</p>
+          </div>
+          <svg class="w-5 h-5 text-purple-600" fill="none" stroke="currentColor" viewBox="0 0 24 24">
+            <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 19v-6a2 2 0 00-2-2H5a2 2 0 00-2 2v6a2 2 0 002 2h2a2 2 0 002-2zm0 0V9a2 2 0 012-2h2a2 2 0 012 2v10m-6 0a2 2 0 002 2h2a2 2 0 002-2m0 0V5a2 2 0 012-2h2a2 2 0 012 2v14a2 2 0 01-2 2h-2a2 2 0 01-2-2z"/>
+          </svg>
+        </a>
       </div>
     </section>