- README.md: Project overview - requirements.md: Full feature specification - competitors.md: Market research (Wealthbox, Affinity, Clay, etc.) - feasibility.md: Technical assessment with Swift/Firebase/Claude architecture - blueprint.md: Architecture diagrams, screens, data models, API endpoints, dev phases Client: David DePoyster / NWM Tech: Swift/SwiftUI, Firebase, Claude AI
461 lines
14 KiB
Markdown
461 lines
14 KiB
Markdown
# The Network App - Technical Feasibility Assessment
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**Date:** 2025-06-26
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**Purpose:** Evaluate technical approach, architecture, and development requirements
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---
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## Executive Summary
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The Network App is **technically feasible** with the proposed stack (Swift/SwiftUI, Firebase, Claude AI). The project is moderate complexity with well-understood patterns. Main challenges are AI integration quality and compliance implementation. Estimated timeline: **12-16 weeks for MVP**.
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---
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## 1. Swift/SwiftUI Architecture Recommendations
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### Platform Choice: Native iOS ✅
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**Why Native:**
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- Best performance for data-heavy CRM
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- Full access to iOS features (biometrics, contacts, notifications)
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- SwiftUI is mature and production-ready (iOS 16+)
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- Offline-first capabilities easier to implement
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- Better for sensitive data handling
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**Why NOT Cross-Platform:**
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- Single platform requirement (iOS first)
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- Native gives compliance advantages
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- No need to compromise on UX
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### Recommended Architecture: MVVM + Clean Architecture
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```
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┌─────────────────────────────────────────────────────┐
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│ Presentation │
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│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
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│ │ Views │ │ ViewModels │ │ Router │ │
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│ │ (SwiftUI) │ │ (ObsObj) │ │ (Coordinat) │ │
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│ └─────────────┘ └─────────────┘ └─────────────┘ │
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├─────────────────────────────────────────────────────┤
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│ Domain │
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│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
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│ │ Use Cases │ │ Entities │ │ Repositories│ │
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│ │ │ │ (Models) │ │ (Protocols) │ │
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│ └─────────────┘ └─────────────┘ └─────────────┘ │
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├─────────────────────────────────────────────────────┤
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│ Data │
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│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
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│ │ Firebase │ │ Claude │ │ Local │ │
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│ │ Service │ │ Service │ │ Cache │ │
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│ └─────────────┘ └─────────────┘ └─────────────┘ │
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└─────────────────────────────────────────────────────┘
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```
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### Key SwiftUI Patterns
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1. **State Management:** Combine + ObservableObject
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2. **Navigation:** NavigationStack (iOS 16+)
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3. **Data Flow:** Single source of truth in ViewModels
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4. **Dependency Injection:** Protocol-based for testability
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### iOS Version Target
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- **Minimum:** iOS 16.0
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- **Reason:** NavigationStack, modern SwiftUI features
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- **Coverage:** ~95% of active iPhones
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---
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## 2. Firebase Structure for Client Data
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### Why Firebase ✅
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**Advantages:**
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- Real-time sync built-in
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- Offline persistence automatic
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- Authentication included
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- Cloud Functions for backend logic
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- Good security rules system
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- Scales automatically
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**Considerations:**
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- NoSQL requires careful data modeling
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- Compliance certifications available (SOC 2, ISO 27001)
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- Data residency options exist
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### Firestore Data Model
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```
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users/
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{userId}/
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profile: { name, email, settings }
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subscription: { tier, expires }
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clients/
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{clientId}/
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userId: string (owner reference)
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basic: {
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firstName, lastName, email, phone
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address: { street, city, state, zip }
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}
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professional: {
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company, role, industry
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}
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personal: {
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birthday, anniversary
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interests: []
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family: { spouse, children: [] }
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preferences: {}
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}
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notes: [] // Array of timestamped notes
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tags: []
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matchPreferences: {
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excludeFromMatching: boolean
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excludeClientIds: []
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}
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metadata: {
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createdAt, updatedAt, lastContactedAt
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}
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communications/
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{communicationId}/
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userId: string
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clientId: string
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type: "email" | "newsletter" | "birthday"
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status: "draft" | "approved" | "sent"
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aiGenerated: {
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content: string
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generatedAt: timestamp
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promptUsed: string
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}
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finalContent: string
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sentAt: timestamp
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matches/
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{matchId}/
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userId: string
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client1Id: string
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client2Id: string
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aiReasoning: string
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score: number
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status: "suggested" | "approved" | "introduced" | "rejected"
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introducedAt: timestamp
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outcome: string
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events/
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{eventId}/
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userId: string
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clientId: string
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type: "birthday" | "anniversary" | "followup" | "custom"
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date: timestamp
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recurring: boolean
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reminderDays: number
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lastTriggered: timestamp
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```
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### Security Rules Strategy
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```javascript
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// Firestore Security Rules (simplified)
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rules_version = '2';
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service cloud.firestore {
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match /databases/{database}/documents {
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// Users can only access their own data
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match /clients/{clientId} {
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allow read, write: if request.auth != null
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&& resource.data.userId == request.auth.uid;
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}
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// Audit log - write only
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match /auditLog/{logId} {
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allow create: if request.auth != null;
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allow read: if false; // Only via admin SDK
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}
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}
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}
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```
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### Offline Strategy
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1. **Firestore Persistence:** Enable by default
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2. **Optimistic Updates:** UI updates immediately
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3. **Conflict Resolution:** Last-write-wins for most fields
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4. **Sync Indicator:** Show pending changes to user
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---
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## 3. Claude AI Integration Approach
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### API Integration Architecture
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```
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┌─────────────┐ ┌─────────────┐ ┌─────────────┐
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│ iOS App │────▶│ Firebase │────▶│ Claude API │
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│ │ │ Functions │ │ │
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└─────────────┘ └─────────────┘ └─────────────┘
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│
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API Key secured
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in Cloud Functions
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```
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**Why Cloud Functions Proxy:**
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- API key never on device
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- Rate limiting and cost control
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- Audit logging for compliance
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- Can cache/optimize requests
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### Claude Use Cases & Prompts
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#### 1. Personalized Email Generation
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```
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System: You are a professional wealth advisor writing to a valued client.
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Maintain a warm but professional tone. Incorporate personal details naturally.
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Context:
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- Advisor name: {advisorName}
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- Client: {clientName}
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- Their interests: {interests}
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- Recent notes: {recentNotes}
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- Purpose: {emailPurpose}
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Generate a personalized email that feels genuine, not templated.
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```
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#### 2. Client Match Suggestions
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```
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System: You are analyzing client profiles to identify valuable networking
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opportunities. Only suggest matches that would genuinely benefit both parties.
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Client A: {profileA}
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Client B: {profileB}
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Evaluate potential match:
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1. What shared interests or complementary needs exist?
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2. How might they benefit from knowing each other?
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3. Confidence score (1-10) with reasoning
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4. Suggested introduction approach
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Output as JSON: { score, reasoning, introductionSuggestion }
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```
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#### 3. Birthday/Event Messages
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```
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System: Generate a thoughtful birthday message from a wealth advisor to
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their client. Should feel personal, not generic.
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Client: {clientName}
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Relationship tenure: {yearsSinceClient}
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Interests: {interests}
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Last interaction: {lastNote}
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Keep it brief (2-3 sentences) and sincere.
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```
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### Cost Estimation
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| Use Case | Tokens/Request | Requests/Month | Monthly Cost |
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|----------|----------------|----------------|--------------|
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| Email generation | ~800 | 200 | ~$2.40 |
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| Match analysis | ~1200 | 100 | ~$1.80 |
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| Birthday messages | ~300 | 50 | ~$0.45 |
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| **Total estimated** | | | **~$5-10/user** |
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*Based on Claude 3.5 Sonnet pricing ($3/M input, $15/M output)*
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### Error Handling
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1. **Timeout:** 30-second limit, show "AI thinking..."
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2. **Failure:** Graceful fallback to templates
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3. **Rate Limits:** Queue and retry with exponential backoff
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4. **Content Filtering:** Review AI output before displaying
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---
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## 4. Security & Compliance Considerations
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### GDPR Compliance
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| Requirement | Implementation |
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|-------------|----------------|
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| Right to Access | Export all client data as JSON/PDF |
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| Right to Deletion | Hard delete with cascade (Firebase Admin SDK) |
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| Data Portability | Standard export format |
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| Consent Tracking | Store consent timestamps per client |
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| Data Minimization | Only collect necessary fields |
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### HIPAA Considerations
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If storing health-related notes (e.g., "client mentioned health concerns"):
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1. **BAA with Firebase:** Google offers BAA for Cloud/Firebase
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2. **Encryption:** AES-256 at rest (Firebase default)
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3. **Access Logging:** Audit trail for all data access
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4. **Employee Training:** Document handling procedures
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### Encryption Strategy
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| Layer | Method |
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|-------|--------|
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| In Transit | TLS 1.3 (Firebase default) |
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| At Rest | AES-256 (Firebase default) |
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| Sensitive Fields | Additional client-side encryption (optional) |
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| Local Cache | iOS Keychain for sensitive data |
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### Authentication Flow
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```
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┌──────────────┐ ┌─────────────┐ ┌──────────────┐
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│ App Launch │───▶│ Biometric │───▶│ Firebase │
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│ │ │ (FaceID) │ │ Auth │
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└──────────────┘ └─────────────┘ └──────────────┘
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│
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Fallback to PIN
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```
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### Audit Logging
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Log these events to a write-only collection:
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- User login/logout
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- Client record created/modified/deleted
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- AI generation requested
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- Export performed
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- Data deletion requested
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---
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## 5. Complexity Assessment
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### Feature Complexity Breakdown
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| Feature | Complexity | Effort (days) | Risk |
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|---------|------------|---------------|------|
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| Client CRUD | Low | 5 | Low |
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| Search & Filters | Medium | 4 | Low |
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| Firebase Auth | Low | 2 | Low |
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| Client Profile UI | Medium | 6 | Low |
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| AI Email Generation | Medium | 5 | Medium |
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| AI Matching | High | 8 | Medium |
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| Birthday Tracking | Low | 3 | Low |
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| Push Notifications | Medium | 3 | Low |
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| Offline Support | Medium | 4 | Medium |
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| Compliance Features | Medium | 5 | Medium |
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| Settings & Preferences | Low | 2 | Low |
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### Technical Risks
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| Risk | Probability | Impact | Mitigation |
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|------|-------------|--------|------------|
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| AI quality inconsistent | Medium | High | Prompt iteration, human review |
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| Firebase scaling costs | Low | Medium | Monitor usage, set alerts |
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| iOS approval delays | Low | Medium | Follow guidelines strictly |
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| Offline sync conflicts | Medium | Medium | Clear conflict resolution UX |
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---
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## 6. Timeline Estimate
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### Phase 1: Foundation (Weeks 1-4)
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- Project setup, architecture
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- Firebase configuration
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- Authentication flow
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- Basic client CRUD
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- **Deliverable:** App shell with auth and data persistence
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### Phase 2: Core Features (Weeks 5-8)
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- Client profile UI (full)
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- Search and filtering
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- Notes and tags
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- Event/birthday tracking
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- Push notifications
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- **Deliverable:** Functional CRM without AI
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### Phase 3: AI Integration (Weeks 9-12)
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- Cloud Functions setup
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- AI email generation
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- AI matching algorithm
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- Review/approval workflows
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- **Deliverable:** Full AI features working
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### Phase 4: Polish & Compliance (Weeks 13-16)
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- Compliance features (export, delete)
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- Audit logging
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- UI polish and edge cases
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- Testing and bug fixes
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- App Store preparation
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- **Deliverable:** Production-ready app
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### Total Estimate: 12-16 weeks
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**With buffer for unknowns:** 16-20 weeks
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---
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## 7. Technology Recommendations
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### Recommended Stack
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| Component | Technology | Rationale |
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|-----------|------------|-----------|
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| Language | Swift 5.9+ | Modern, safe, performant |
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| UI | SwiftUI | Declarative, less code |
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| Architecture | MVVM | SwiftUI natural fit |
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| Backend | Firebase | Real-time, offline, scales |
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| Database | Firestore | Flexible schema, good sync |
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| Auth | Firebase Auth | Turnkey, secure |
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| Functions | Cloud Functions | Secure AI proxy |
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| AI | Claude API | Quality, context length |
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| Analytics | Firebase Analytics | Integrated, free |
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| Crash Reporting | Firebase Crashlytics | Integrated, free |
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### Development Tools
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- **Xcode 15+** - Latest SwiftUI features
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- **Swift Package Manager** - Dependency management
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- **SwiftLint** - Code quality
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- **Firebase Emulator** - Local development
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### Third-Party Libraries
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Keep minimal:
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- Firebase iOS SDK
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- (Optional) Kingfisher for image caching
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- (Optional) SwiftUI introspect for edge cases
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---
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## 8. Conclusion
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### Feasibility: ✅ HIGH
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The project is well within established technology patterns. No experimental tech required.
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### Key Success Factors
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1. **AI Prompt Engineering** - Invest time in quality prompts
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2. **UX for AI Review** - Make human approval frictionless
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3. **Offline-First** - Critical for mobile advisor use
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4. **Compliance Documentation** - Start early, not late
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### Recommended Next Steps
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1. Finalize scope and budget
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2. Set up Firebase project
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3. Create Figma designs for key screens
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4. Begin Phase 1 development
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### Cost Summary
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| Item | One-Time | Monthly |
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|------|----------|---------|
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| Development (16 wks) | $15-40K* | - |
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| Firebase (100 users) | - | $25-50 |
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| Claude API (per user) | - | $5-10 |
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| Apple Developer | $99/year | - |
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| **Total Year 1** | ~$15-40K | ~$75-150 |
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*Development cost varies significantly based on who builds it
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