docs: LandveX Intelligence Lab specification v1.0

- Internal development environment for Control Intelligence
- Core principle: 'Produces verified Control Intelligence, not AI models'
- Separate repo: landvex-intelligence-lab
- Navigation: Dashboard, Models, Datasets, Annotations, Training,
  Evaluation, Decision Cases, Replay, Validation, Deploy, Settings

- Key features:
  - Dashboard: AI status (models, datasets, jobs, cases)
  - Mission Replay: click through entire chain
  - Annotation: video + AI suggestion + manual correction
  - Decision Cases: first-class objects, all playable
  - Benchmark: compare YOLO, Grounding DINO, SAM, custom models
  - Replay: find regressions between model versions
  - Validation: field trials, scenario tests, decision tests
  - Deploy: 'Promote Model' not 'Deploy' (dev → validation → pilot → prod)
  - Experiments: link EP-1.0, DS-001, etc. to real data

- Target: New AI engineer understands in minutes:
  'This is where we build, test, and verify LandveX Control Intelligence
   before anything reaches production.'

Rationale: Single internal tool for all AI development. Centralizes
model training, annotation, validation, replay, decision chains,
regression tests, experiments, and model promotion.
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# LANDVEX INTELLIGENCE LAB
**Internal Development Environment for Control Intelligence**
| | |
|---|---|
| **Version** | 1.0 |
| **Status** | SPECIFICATION |
| **Purpose** | Build, test, and verify LandveX Control Intelligence before production |
---
## Core Principle
**LandveX Intelligence Lab does not produce AI models. It produces verified Control Intelligence.**
This is an internal tool. Never a customer product.
---
## Repository
```
landvex-intelligence-lab
```
Separate from:
- `quixzoom-app`
- `landvex-web`
- `aamos-core`
---
## Navigation
```
Dashboard
├── Models
├── Datasets
├── Annotations
├── Training
├── Evaluation
├── Decision Cases
├── Replay
├── Validation
├── Deploy (Promote Model)
└── Settings
```
---
## Dashboard
Shows AI status, not business data.
```
┌─────────────────────────────────────┐
│ Models │
│ Detection v12 │
│ Segmentation v5 │
│ OCR v3 │
│ Decision Model v1.0 │
├─────────────────────────────────────┤
│ Datasets │
│ Roads, Buildings, Signs │
│ Vegetation, Drainage │
├─────────────────────────────────────┤
│ Training Jobs │
│ Running: 2 │
│ Queued: 1 │
│ Failed: 0 │
│ Completed: 47 │
├─────────────────────────────────────┤
│ Decision Cases │
│ Validated: 23 │
│ Pending: 5 │
│ Rejected: 2 │
└─────────────────────────────────────┘
```
---
## Mission Replay
Click through the entire chain:
```
Video → Frame → Bounding boxes → Detected objects → Evidence → Finding → Decision → Business Impact
```
---
## Annotation
```
┌─────────┬─────────────┬──────────────┐
│ Video │ AI Suggestion│ Manual │
│ │ │ Correction │
├─────────┼─────────────┼──────────────┤
│ │ Object: │ Correct? │
│ │ Road Crack │ YES / NO │
│ │ Confidence: │ │
│ │ 82% │ Severity: │
│ │ │ Low / Medium │
│ │ │ / High │
└─────────┴─────────────┴──────────────┘
```
---
## Decision Case
First-class objects:
```
Case #4232
├── Reality
├── Observation
├── Evidence
├── Finding
├── Decision
├── Outcome
└── Learning
```
All cases playable.
---
## Benchmark
Compare models:
| Model | Precision | Recall | F1 | Latency | Decision Accuracy |
|-------|-----------|--------|----|---------|-------------------|
| YOLO v8 | 0.89 | 0.87 | 0.88 | 45ms | — |
| Grounding DINO | 0.91 | 0.85 | 0.88 | 120ms | — |
| SAM | 0.88 | 0.90 | 0.89 | 200ms | — |
| Custom | 0.92 | 0.91 | 0.915 | 60ms | 0.87 |
---
## Replay
Find regressions:
```
Mission 213
├── Play
├── Show AI
├── Show Human Annotation
├── Differences
├── New Model
└── Old Model
```
---
## Validation
```
Field Trials
Scenario Tests
Decision Tests
Evidence Tests
Golden Failures
Regression Tests
```
---
## Deploy (Promote Model)
```
Development → Validation → Pilot → Production
```
Not "Deploy". "Promote Model".
---
## Experiments
```
Experiments
├── EP-1.0
├── DS-001
├── DS-002
├── DS-003
├── Field Trials
└── Metrics
```
Link experiment protocol to real development and validation data.
---
## What This Tool Collects
- Model training
- Annotation
- Datasets
- Replay
- Decision chains
- Validation
- Regression tests
- Experiments
- Model promotion
---
## New Developer Experience
A new AI engineer should open the repo and within minutes understand:
**"This is the tool where we build, test, and verify LandveX Control Intelligence before anything reaches production."**
---
## Relationship to Principles
- All development in Git
- All experiments reproducible
- All models traceable from training to validation to production
- Version control and traceability
---
## ändringshistoria
| Version | Datum | Beskrivning |
|---------|-------|-------------|
| 1.0 | 2026-07-02 | Initial specification for LandveX Intelligence Lab |
---
## STATUS
**SPECIFICATION — Awaiting development decision**