# EmboFlow V1 Scope And MVP

## MVP Definition

The first release should prove that EmboFlow can turn raw embodied data assets into structured outputs through a visual workflow engine.

### MVP Success Path

1. A user signs into a workspace
2. The user creates a project
3. The user uploads or imports a raw asset
4. The platform probes the asset and generates a structure summary
5. The user previews the asset
6. The user composes a canvas workflow
7. The workflow executes asynchronously
8. The user reviews logs, outputs, and generated artifacts
9. The user exports a normalized dataset, delivery package, or training config

## In Scope For V1

- User login and workspace model
- Personal and team workspaces
- Project resource isolation
- Raw asset upload and import
- Object storage integration
- Asset probing and structure detection
- Raw asset preview
- Canvas workflow editor
- Built-in node library for ingest, transform, inspect, export
- Node configuration through schema-driven forms
- Code injection for processing nodes
- Workflow run orchestration
- Logs, status, retries, and artifact tracking
- Dataset conversion and delivery-package normalization
- Training config export
- Plugin registration skeleton

## Important Business Scenarios

### Embodied Dataset Conversion

- Import RLDS, LeRobot, HDF5, or Rosbag
- Map to canonical semantics
- Export to target dataset format

### Delivery Package Normalization

- Import customer-provided raw directory or archive
- Rename top-level folders
- Validate required file structure
- Validate metadata files
- Check video file quality and naming
- Export or upload normalized package

### Data Processing Workflow Authoring

- Drag nodes onto canvas
- Connect nodes into DAG
- Tune parameters
- Inject code into processing nodes
- Re-run pipeline with traceable history

## V1 Modules To Build Deeply

- Identity and workspace management
- Asset ingestion and probing
- Workflow editor and node model
- Execution engine
- Built-in dataset conversion nodes
- Built-in delivery normalization nodes
- Preview and inspection
- Artifact export

## V1 Modules To Keep Lightweight

- Annotation
- Collaboration
- Plugin lifecycle UX
- Advanced analytics
- Kubernetes and Volcano scheduling adapters
- Advanced multi-sensor synchronized visual analytics

## Explicit V1 Exclusions

- Platform-managed training execution
- Real-time multi-user canvas co-editing
- Full marketplace for third-party plugins
- Complex enterprise approval workflows
- Streaming data processing
- Large-scale distributed execution as a deployment requirement