docs: LandveX Intelligence Lab v1.2 — MVP + Phases + Data Quality + Decision Analytics
- MVP Milestone: 'First Verified Decision'
- Developer films with quiXzoom, imports to Lab, corrects AI,
creates Decision Case, follows chain with full traceability
- When this works = first complete verifiable Control Intelligence pipeline
- Three development phases:
Phase 1 (Essential): Ingestion, Dataset Explorer, Annotation, Decision Case Viewer
Phase 2 (Scale): Replay, Benchmark, Evaluation
Phase 3 (Advanced): GPU Jobs, Hyperparameter Runs, Model Promotion, Canary
- Product Architecture: quiXzoom → Observations → Intelligence Lab →
Improved Models → LandveX → Better Decisions → Feedback → Intelligence Lab
- Two products: quiXzoom (observations), LandveX (decisions)
- Intelligence Lab = the factory that improves both
- New areas:
- Data Quality: Healthy/Blurred/Duplicate/Wrong GPS/Night/Rain/Occluded
+ Coverage (Roads, Buildings, Signs, Drainage, Vegetation)
- Decision Analytics: Acceptance Rate, Ignore Rate, Accuracy,
Insufficient Evidence, Data Collection Value
- Business value metrics, not traditional AI metrics
Rationale: Build MVP first, prove first real workflow, then scale.
Decision Cases are the heart. Data Quality explains model performance.
Decision Analytics measure business value.
This commit is contained in:
@@ -26,6 +26,31 @@ This is an internal tool. Never a customer product.
|
|||||||
|
|
||||||
**Every change must be traceable to a specific experiment, model version, dataset, and decision.**
|
**Every change must be traceable to a specific experiment, model version, dataset, and decision.**
|
||||||
|
|
||||||
|
## Product Architecture
|
||||||
|
|
||||||
|
```
|
||||||
|
quiXzoom
|
||||||
|
↓
|
||||||
|
Observations
|
||||||
|
↓
|
||||||
|
LandveX Intelligence Lab
|
||||||
|
↓
|
||||||
|
Improved Models
|
||||||
|
↓
|
||||||
|
LandveX
|
||||||
|
↓
|
||||||
|
Better Decisions
|
||||||
|
↓
|
||||||
|
Feedback
|
||||||
|
↓
|
||||||
|
Intelligence Lab
|
||||||
|
```
|
||||||
|
|
||||||
|
**Two products:**
|
||||||
|
- **quiXzoom** — produces observations
|
||||||
|
- **LandveX** — produces decisions
|
||||||
|
- **Intelligence Lab** — the factory that improves both
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
## Repository
|
## Repository
|
||||||
@@ -353,11 +378,95 @@ A new AI engineer should open the repo and within minutes understand:
|
|||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
|
## MVP Milestone: "First Verified Decision"
|
||||||
|
|
||||||
|
**Definition:**
|
||||||
|
A developer can:
|
||||||
|
1. Film a real object with quiXzoom
|
||||||
|
2. Import material to Intelligence Lab
|
||||||
|
3. Review and correct AI interpretation
|
||||||
|
4. Create a Decision Case
|
||||||
|
5. Follow the entire chain from observation to decision with full traceability
|
||||||
|
|
||||||
|
**When this works, you have the first complete, verifiable Control Intelligence pipeline.**
|
||||||
|
|
||||||
|
## Development Phases
|
||||||
|
|
||||||
|
### Phase 1 — Essential (for pilot missions)
|
||||||
|
|
||||||
|
| Feature | Purpose |
|
||||||
|
|---------|---------|
|
||||||
|
| **Ingestion** | Upload images/video, show metadata (GPS, time, device), store raw data immutably |
|
||||||
|
| **Dataset Explorer** | Browse missions, filter, search, open a mission |
|
||||||
|
| **Annotation** | AI suggestions, manual correction, version history |
|
||||||
|
| **Decision Case Viewer** | Observation → Evidence → Finding → Decision → Business Impact → Learning |
|
||||||
|
|
||||||
|
**This is the heart.**
|
||||||
|
|
||||||
|
### Phase 2 — Scale (when running many missions)
|
||||||
|
|
||||||
|
| Feature | Purpose |
|
||||||
|
|---------|---------|
|
||||||
|
| **Replay** | Compare model versions on same mission |
|
||||||
|
| **Benchmark** | Model comparisons |
|
||||||
|
| **Evaluation** | Regression tests |
|
||||||
|
|
||||||
|
### Phase 3 — Advanced (when having multiple models)
|
||||||
|
|
||||||
|
| Feature | Purpose |
|
||||||
|
|---------|---------|
|
||||||
|
| **GPU Jobs** | Training queue |
|
||||||
|
| **Hyperparameter Runs** | Automated experiments |
|
||||||
|
| **Model Promotion** | Development → Validation → Pilot → Production |
|
||||||
|
| **Canary Releases** | Gradual rollout |
|
||||||
|
|
||||||
|
## New Areas
|
||||||
|
|
||||||
|
### Data Quality
|
||||||
|
|
||||||
|
Before training anything:
|
||||||
|
|
||||||
|
```
|
||||||
|
Images
|
||||||
|
├── Healthy
|
||||||
|
├── Blurred
|
||||||
|
├── Duplicate
|
||||||
|
├── Wrong GPS
|
||||||
|
├── Night
|
||||||
|
├── Rain
|
||||||
|
└── Occluded
|
||||||
|
```
|
||||||
|
|
||||||
|
Coverage:
|
||||||
|
```
|
||||||
|
Roads, Buildings, Signs, Drainage, Vegetation
|
||||||
|
```
|
||||||
|
|
||||||
|
Quickly shows why a model performs well or poorly.
|
||||||
|
|
||||||
|
### Decision Analytics
|
||||||
|
|
||||||
|
Not AI metrics. Decision metrics.
|
||||||
|
|
||||||
|
| Metric | Question |
|
||||||
|
|--------|----------|
|
||||||
|
| Acceptance Rate | How many recommendations were accepted? |
|
||||||
|
| Ignore Rate | How many were ignored? |
|
||||||
|
| Accuracy | How many proved correct? |
|
||||||
|
| Insufficient Evidence | How many lacked enough evidence? |
|
||||||
|
| Data Collection Value | How often did "Collect more data" lead to a better decision? |
|
||||||
|
|
||||||
|
Closer to LandveX business value than traditional AI metrics.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
## ändringshistoria
|
## ändringshistoria
|
||||||
|
|
||||||
| Version | Datum | Beskrivning |
|
| Version | Datum | Beskrivning |
|
||||||
|---------|-------|-------------|
|
|---------|-------|-------------|
|
||||||
| 1.0 | 2026-07-02 | Initial specification for LandveX Intelligence Lab |
|
| 1.0 | 2026-07-02 | Initial specification for LandveX Intelligence Lab |
|
||||||
|
| 1.1 | 2026-07-02 | Added architecture, pipelines, immutability |
|
||||||
|
| 1.2 | 2026-07-02 | Added MVP milestone, development phases, Data Quality, Decision Analytics |
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
|
|||||||
Reference in New Issue
Block a user