# Business Architecture Overview

## Strategic Themes

- accelerate scientific reporting with trusted AI
- improve traceability, compliance, and metadata quality

## Value Streams

1. Study data intake
2. AI-assisted reporting
3. Validation and review
4. Traceability and audit
5. Lineage and metadata governance

## Business Capabilities

### Data and Intake

- study intake management
- evidence curation
- metadata normalization

### AI Reporting

- report drafting
- AI recommendation management
- scientific search and retrieval
- citation grounding

### Validation and Governance

- validation review
- human approval
- compliance verification
- audit trail management

### Intelligence and Operations

- KPI monitoring
- connector health monitoring
- workflow orchestration
- lineage management
- metadata governance

## Persona Set

- regulatory writer
- data steward
- AI ops admin
- leadership or program owner

## Simplified Workflow

```mermaid
flowchart LR
  A["Study Data Intake"] --> B["AI-Assisted Reporting"]
  B --> C["Validation and Review"]
  C --> D["Traceability and Audit"]
  D --> E["Lineage and Metadata Governance"]
```

## Touchpoints

- executive dashboard
- reporting workspace
- validation workspace
- scientific search portal
- audit and KPI console
- lineage and metadata intelligence
- GenAI copilot sidebar

## Business Outcomes

- shorter report cycle time
- higher groundedness and trust
- better traceability and compliance
- improved metadata completeness
- reduced manual effort
- stronger decision support