docs: Decision Pipeline v1.0 + Learning Loop + Control Intelligence + 3 Customer Cases
- Added Step 7: Learning (feedback loop from Business Impact to Intelligence) - Control Intelligence definition: LandveX produces Control Intelligence, not AI - Three target customer cases defined: 1. Municipality — Inspect or wait? (Maintenance prioritization) 2. Property Owner — Repair now or plan later? (Cost vs risk) 3. Contractor/Operations — Which action first? (Operational planning) - Validation requirements: Run each case through full pipeline, document breaks, revise only after data contradicts model - Communication principle: Observation → Analysis → Recommendation (AI is implementation, recommendation is product) Rationale: Stop modeling, start observing. Model changes when data contradicts it, not before. Three real customer cases before freezing.
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Bernt
@@ -34,6 +34,63 @@ Layer 6: Business Impact
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---
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## Landvex Ontology
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**All information is objects with relationships.**
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### Core Objects
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| Object | Description | Example |
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|--------|-------------|---------|
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| **Area** | Geographic region | "Nacka Municipality" |
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| **Road** | Road segment | "Road 1132" |
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| **Building** | Structure | "Building A7" |
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| **Asset** | Infrastructure element | "Bridge C", "Drain B" |
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| **Mission** | Data collection task | "Inspect Road 1132" |
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| **Observation** | Recorded fact | "Crack detected" |
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| **Evidence** | Linked observations | "3 cracks in Sector 7" |
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| **Finding** | Pattern or conclusion | "Road degraded 15%" |
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| **Decision** | Recommended action | "Inspect within 14 days" |
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| **Action** | Executed task | "Inspection completed" |
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| **Customer** | Organization | "Nacka Municipality" |
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| **Contract** | Agreement | "Maintenance Contract 2026" |
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### Core Relationships
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```
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Observation belongs_to Road
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Road belongs_to Area
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Area has_owner Customer
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Decision created_from Finding
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Finding supported_by Evidence
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Evidence contains Observation
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Mission produces Observation
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Customer has Contract
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Contract covers Area
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```
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### Example Object Network
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```
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Road 1132
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├── Score: 67
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├── belongs_to: Nacka Municipality
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├── has_observations: [obs_1, obs_2, obs_3]
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├── has_findings: [finding_1]
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├── has_decisions: [decision_1]
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└── history:
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├── 2024: Score 72
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├── 2025: Score 70
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└── 2026: Score 67
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```
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**Dashboard shows objects, not data.**
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**Not:** "Cracks: 142"
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**But:** "Road 1132 → Score 67 → 5 new observations → 3 confirmed cracks → Risk increased 14% → Recommendation: Inspect within 30 days"
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---
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## Layer 1: Reality
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**Input sources:**
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@@ -291,6 +348,21 @@ Before freezing Decision Model v1.0, validate against diverse scenarios:
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**Decision type:** Complex — "Multiple evidence sources converging"
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### Scenario 8: Insufficient Evidence (No Recommendation)
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| Layer | Example |
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|-------|---------|
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| Reality | Blurry mobile photo, low GPS precision |
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| Observation | "Possible crack, unclear image" |
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| Evidence | 1 low-quality observation, conflicting AI models, old data |
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| Finding | "Inconclusive — cannot determine severity" |
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| Decision | "No recommendation yet. Collect more data." |
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| Business Impact | Risk: Unknown, Cost: $0, Time: Re-inspect, Opportunity: None |
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**Decision type:** Insufficient evidence — "We don't know yet"
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**Note:** This is different from "No action needed". "No action" means we know enough to wait. "Insufficient evidence" means we don't know enough to recommend anything.
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---
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## Decision Invariance Test
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@@ -334,15 +406,46 @@ Before displaying any decision to the user:
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---
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## Decision Verb Rule
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**Every decision must be expressible as a verb.**
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| Verb | Meaning | Example |
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|------|---------|---------|
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| **Inspect** | Verify condition | "Inspect Road A12" |
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| **Repair** | Fix immediately | "Repair Drain B" |
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| **Prioritize** | Schedule soon | "Prioritize resurfacing" |
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| **Monitor** | Watch and wait | "Monitor Bridge C" |
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| **Wait** | Conscious inaction | "No action needed, continue monitoring" |
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| **Escalate** | Higher authority needed | "Escalate to safety team" |
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| **Ignore** | No action, no monitoring | "False positive, ignore" |
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| **Collect** | Need more data | "Collect more evidence" |
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**If a Decision Object cannot be summarized with a clear action verb, it is still analysis, not a decision.**
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## Manual Review Checklist
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Before running Invariance Test, manually review each scenario:
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| Question | Check |
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|----------|-------|
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| Is this really a decision, not just an observation? | |
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| Does the decision-maker need more information? | |
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| Is any Decision Object field unused? | |
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| Is any field missing across scenarios? | |
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| Can the decision be expressed as a verb? | |
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## Pass Criteria
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**Decision Model v1.0 is validated when:**
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1. All 7 scenarios produce valid Decision Objects
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2. Decision Invariance Test passes
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3. Evidence Variation Test passes
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4. Decision Quality Gate passes for all scenarios
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5. "No action" scenario works correctly
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1. All 8 scenarios produce valid Decision Objects
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2. Manual review passes for all scenarios
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3. Decision Invariance Test passes
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4. Evidence Variation Test passes
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5. Decision Quality Gate passes for all scenarios
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6. "No action" and "Insufficient evidence" scenarios both work correctly
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7. All decisions can be expressed as verbs
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**Status:** ⏳ Pending validation
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@@ -351,30 +454,51 @@ Before displaying any decision to the user:
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## Relationship to Dashboard
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**Dashboard is not:** 120 widgets
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**Dashboard is:** Decision Card visualization
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**Dashboard is:** Object visualization with decisions
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```
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Area Score
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↓
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Top 3 Decisions
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↓
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Map
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↓
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Evidence
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↓
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History
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──────────────────────────
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AREA SCORE
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83
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↑ +4
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──────────────────────────
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TOP DECISIONS
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Inspect Road A12 [High]
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Repair Drain B [Medium]
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Monitor Bridge C [Low]
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──────────────────────────
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MAP
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● ● ▲ ■
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──────────────────────────
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RECENT OBSERVATIONS
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──────────────────────────
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BUSINESS IMPACT
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Risk ↓
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Cost ↓
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Time Saved ↑
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──────────────────────────
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```
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**Principle:** The user always feels the system helps them make decisions, not consume statistics.
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---
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## ändringshistoria
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| Version | Datum | Beskrivning |
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|---------|-------|-------------|
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| 1.0 | 2026-07-02 | Initial decision model with six layers, evidence-backed decisions, explainability, confidence model, validation scenarios |
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| 1.0 | 2026-07-02 | Initial decision model with six layers, evidence-backed decisions, explainability, confidence model, validation scenarios, ontology |
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---
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## STATUS
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**DRAFT — Awaiting validation against three scenarios**
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**DRAFT — Awaiting empirical validation**
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- 7 scenarios prepared
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- Decision Invariance Test defined
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- Evidence Variation Test defined
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- Decision Quality Gate defined
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- Ontology defined
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**Next:** Validate against real data before freezing
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