Estimation Matrix
A consolidated itemization of all 400+ Use Cases for effort estimation, categorized by module and complexity.
Phase Legend:
MVP= Phase 1 |P2= Phase 2 |P3= Phase 3 |P4= Phase 4
Effort Estimation Legend
| Complexity | Type | Man-Hours |
|---|---|---|
| Simple | Core UI, Basic CRUD | 4-8 |
| Medium | Logic, Validation, Integration | 8-16 |
| Complex | AI/ML Rules, Multi-system | 16-24 |
| Advanced | ML Models, NLP, GenAI | 24-40 |
1. Appointments Calendar (Stylist Slot View)
Total: 44 Use Cases | MVP: 20 | P2+: 24 | MVP Effort: 166 hrs (adjusted -10%)
| ID | Capability | Category | Type | Phase | Hrs |
|---|---|---|---|---|---|
| Core Functional | |||||
| 1.1 | View daily appointment grid by stylist | Frontend | Core | MVP | 7 |
| 1.2 | Navigate date forward/backward | Frontend | Core | MVP | 3 |
| 1.3 | Time-slot based scheduling | Frontend | Core | MVP | 7 |
| 1.4 | Create new appointment in blank slot | Backend | Core | MVP | 10 |
| 1.5 | Edit existing appointment | Backend | Core | MVP | 7 |
| 1.6 | Cancel appointment | Backend | Core | MVP | 5 |
| 1.7 | Reschedule appointment | Backend | Core | MVP | 7 |
| 1.8 | Block unavailable slots manually | Backend | Core | P2 | - |
| 1.9 | Full-day stylist unavailability | Backend | Core | MVP | 5 |
| 1.10 | Multi-service appointment tagging | Backend | Core | MVP | 10 |
| 1.10a | Multi-service booking (sequential selection) | Backend | Core | MVP | 14 |
| 1.10b | Search appointments (client name/phone/provider) | Frontend | Core | MVP | 10 |
| 1.11 | Gender/service category filtering | Frontend | Core | P2 | - |
| 1.12 | Customer name + service display | Frontend | Core | MVP | 5 |
| 1.13 | Overbooking prevention | Backend | Logic | MVP | 10 |
| 1.14 | Double-booking validation | Backend | Logic | MVP | 10 |
| 1.15 | Walk-in appointment allocation | Backend | Core | MVP | 7 |
| 1.16 | Staff-wise load balancing view | Frontend | Core | P2 | - |
| 1.17 | Color-coded service visualization | Frontend | UI | P2 | - |
| 1.18 | Conflict detection on move | Backend | Logic | MVP | 10 |
| 1.19 | Drag & drop rescheduling | Frontend | UI | P3 | - |
| 1.20 | Appointment notes / remarks | Backend | Core | MVP | 5 |
| 1.21 | Service duration auto-calculation | Backend | Logic | MVP | 7 |
| 1.22 | Buffer time handling | Backend | Logic | P2 | - |
| 1.23 | Auto slot extension (premium) | Backend | Logic | P3 | - |
| 1.24 | No-show marking | Backend | Core | MVP | 5 |
| 1.25 | Late arrival marking | Backend | Core | P2 | - |
| AI / Intelligence | |||||
| 1.26 | Predict service overrun risk | AI/ML | Model | P3 | - |
| 1.27 | Suggest optimal stylist | AI/ML | Logic | P2 | - |
| 1.28 | Predict no-show probability | AI/ML | Model | P2 | - |
| 1.29 | Auto-rebook suggestions | AI/ML | Logic | P2 | - |
| 1.30 | Dynamic slot pricing | AI/ML | Logic | P3 | - |
| 1.31 | Smart overbooking windows | AI/ML | Logic | P3 | - |
| 1.32 | Peak hour prediction | AI/ML | Model | P2 | - |
| 1.33 | Idle slot forecasting | AI/ML | Model | P2 | - |
| Analytics | |||||
| 1.34 | Chair occupancy rate | Analytics | Metric | MVP | 7 |
| 1.35 | Stylist utilization | Analytics | Metric | P2 | - |
| 1.36 | Avg service duration | Analytics | Metric | P2 | - |
| 1.37 | Cancellation heatmap | Analytics | Viz | P3 | - |
| 1.38 | Revenue per hour | Analytics | Metric | P2 | - |
| Integrations | |||||
| 1.39 | WhatsApp confirmation | Integration | API | MVP | 5 |
| 1.40 | SMS reminders | Integration | API | P2 | - |
| 1.41 | Google Calendar sync | Integration | API | P2 | - |
| 1.42 | POS sync | Integration | API | MVP | 7 |
2. Marketing Studio - Message Generator
Total: 23 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 2.1 | Enter campaign intent | Frontend | Core |
| 2.2 | Select tone | Frontend | UI |
| 2.3 | Select target audience | Backend | Logic |
| 2.4 | Generate 3 variants | Backend | Core |
| 2.5 | Copy option | Frontend | UI |
| 2.6 | Regenerate messages | Backend | Core |
| 2.7 | Multi-language generation | Backend | Core |
| 2.8 | Save template | Backend | Core |
| 2.9 | Reuse past campaigns | Backend | Core |
| 2.10 | Edit generated text | Frontend | Core |
| 2.11 | Character limit enforcement | Frontend | Logic |
| 2.12 | CTA auto-injection | Backend | Logic |
| 2.13 | Hashtag generator | Backend | Logic |
| 2.14 | Emoji suggestions | Backend | Logic |
| AI / Intelligence | |||
| 2.15 | High conversion copy prediction | AI/ML | Model |
| 2.16 | Personalization variables | AI/ML | Logic |
| 2.17 | Seasonal relevance detection | AI/ML | Logic |
| 2.18 | Festival campaign adaptation | AI/ML | Logic |
| 2.19 | Urgency optimization | AI/ML | Logic |
| 2.20 | A/B text optimization | AI/ML | Logic |
| 2.21 | Offer optimization history | AI/ML | Model |
| Social Media Integration | |||
| 2.22 | Post directly to Instagram | Integration | API |
| 2.23 | Post directly to Facebook | Integration | API |
3. Marketing Studio - Image Generator
Total: 17 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 3.1 | Platform selection | Frontend | UI |
| 3.2 | Creative type selection | Frontend | UI |
| 3.3 | Generate image | Backend | Core |
| 3.4 | Preview creative | Frontend | UI |
| 3.5 | Download creative | Frontend | Core |
| 3.6 | Re-generate variation | Backend | Core |
| 3.7 | Resize for platforms | Backend | Logic |
| 3.8 | Logo auto insertion | Backend | Logic |
| 3.9 | Brand color enforcement | Backend | Logic |
| 3.10 | Offer text overlay | Backend | Logic |
| 3.11 | Service image auto-pick | Backend | Logic |
| 3.12 | Before-after layout | Backend | Logic |
| AI / Intelligence | |||
| 3.13 | Visual CTR prediction | AI/ML | Model |
| 3.14 | Aesthetic scoring | AI/ML | Model |
| 3.15 | Facial symmetry optimization | AI/ML | Logic |
| 3.16 | Demographic targeting visuals | AI/ML | Logic |
| 3.17 | Festival-adaptive themes | AI/ML | Logic |
4. Staff Management - Leave Scheduling
Total: 19 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 4.1 | Select staff | Frontend | Core |
| 4.2 | Select date | Frontend | UI |
| 4.3 | Full-day leave | Backend | Core |
| 4.4 | Partial-day leave | Backend | Core |
| 4.5 | Time-bound slots | Backend | Core |
| 4.6 | Save leave | Backend | Core |
| 4.7 | Edit leave | Backend | Core |
| 4.8 | Cancel leave | Backend | Core |
| 4.9 | View upcoming leaves | Frontend | Core |
| 4.10 | Conflict detection | Backend | Logic |
| 4.11 | Auto-block slots | Backend | Logic |
| 4.12 | Multi-day leave | Backend | Core |
| 4.13 | Emergency override | Backend | Logic |
| 4.14 | Leave reason tagging | Backend | Core |
| 4.15 | Approval workflow | Backend | Logic |
| 4.16 | Leave audit log | Backend | Core |
| AI / Intelligence | |||
| 4.17 | Auto substitute assignment | AI/ML | Logic |
| 4.18 | Leave revenue impact | AI/ML | Model |
| 4.19 | Optimal timing suggestion | AI/ML | Logic |
5. Staff Attendance System
Total: 22 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 5.1 | Daily attendance selection | Frontend | Core |
| 5.2 | Check-in | Backend | Core |
| 5.3 | Check-out | Backend | Core |
| 5.4 | Manual override | Backend | Core |
| 5.5 | Edit incorrect time | Backend | Core |
| 5.6 | Total hours calc | Backend | Logic |
| 5.7 | Absentee marking | Backend | Core |
| 5.8 | Late entry tagging | Backend | Logic |
| 5.9 | Early exit tagging | Backend | Logic |
| 5.10 | Half-day marking | Backend | Core |
| 5.11 | Break tracking | Backend | Core |
| 5.12 | GPS validation | Mobile | Core |
| 5.13 | Geo-fencing | Mobile | Logic |
| 5.14 | Bulk upload | Backend | Core |
| 5.15 | Attendance export | Backend | Ops |
| 5.16 | Payroll sync | Integration | API |
| 5.17 | Correction approval | Backend | Logic |
| 5.18 | Biometric/Face ID | Mobile | Core |
| AI / Intelligence | |||
| 5.19 | Fraud detection | AI/ML | Model |
| 5.20 | Performance correlation | AI/ML | Analytics |
| 5.21 | Burnout risk | AI/ML | Model |
| 5.22 | Shift optimization | AI/ML | Logic |
6. Revenue Actionables Dashboard (Business Analytics)
Total: 25 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 6.1 | Revenue target setup | Backend | Core |
| 6.2 | Real-time booked revenue | Analytics | Metric |
| 6.3 | Gap calculation | Analytics | Metric |
| 6.4 | Progress bar | Frontend | Viz |
| 6.5 | Manual target change | Backend | Core |
| 6.6 | WhatsApp trigger | Integration | API |
| 6.7 | Offer injection | Backend | Logic |
| 6.8 | Service mix rec | Analytics | Logic |
| 6.9 | Revenue by service | Analytics | Metric |
| 6.10 | Revenue by stylist | Analytics | Metric |
| 6.11 | Revenue by hour | Analytics | Metric |
| 6.12 | Refund handling | Backend | Core |
| 6.13 | Discount application | Backend | Logic |
| 6.14 | Tax calculation | Backend | Logic |
| AI / Intelligence | |||
| 6.15 | Revenue recovery strategy | AI/ML | Logic |
| 6.16 | Upsell bundle gen | AI/ML | Logic |
| 6.17 | Price elasticity | AI/ML | Model |
| 6.18 | Gap-to-offer translation | AI/ML | Logic |
| 6.19 | Demand prediction | AI/ML | Model |
| 6.20 | Conversion probability | AI/ML | Model |
| 6.21 | Smart discount selection | AI/ML | Logic |
| Business Analytics Dashboard (MVP) | |||
| 6.22 | Gross Sales & Net Revenue display | Analytics | Metric |
| 6.23 | Staff Utilization % | Analytics | Metric |
| 6.24 | Booking Conversion Rate | Analytics | Metric |
| 6.25 | Period comparison (WoW, MoM) | Analytics | Viz |
7. Empty Chair Rescue
Total: 13 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 7.1 | Detect dead slots | Backend | Logic |
| 7.2 | Show service tags | Frontend | UI |
| 7.3 | Show slot duration | Frontend | UI |
| 7.4 | Priority marking | Backend | Logic |
| 7.5 | One-click push | Integration | API |
| 7.6 | Push multiple offers | Integration | API |
| 7.7 | Offer expiry timer | Backend | Logic |
| 7.8 | Location-based push | Integration | API |
| 7.9 | Client eligibility filter | Backend | Logic |
| AI / Intelligence | |||
| 7.10 | Nearest high-prob client | AI/ML | Model |
| 7.11 | Dynamic pricing (idle) | AI/ML | Logic |
| 7.12 | Psychological anchoring | AI/ML | Logic |
| 7.13 | Service bundling AI | AI/ML | Logic |
8. AI Call Recommendations
Total: 12 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 8.1 | Identify non-booked clients | Backend | Logic |
| 8.2 | Show last visit gap | Frontend | UI |
| 8.3 | Call button | Integration | Mobile |
| 8.4 | WhatsApp button | Integration | API |
| 8.5 | Multi-client batch | Frontend | UI |
| 8.6 | Script preview | AI/ML | GenAI |
| 8.7 | Call outcome tagging | Backend | Core |
| 8.8 | Follow-up reminders | Backend | Logic |
| AI / Intelligence | |||
| 8.9 | Call timing optimization | AI/ML | Model |
| 8.10 | Script personalization | AI/ML | GenAI |
| 8.11 | Booking probability | AI/ML | Model |
| 8.12 | Call fatigue modeling | AI/ML | Model |
9. Customer Goldmine (Dormant)
Total: 14 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 9.1 | Dormant client detection | Analytics | Logic |
| 9.2 | Last service display | Frontend | UI |
| 9.3 | Last spend display | Frontend | UI |
| 9.4 | Days since visit | Frontend | Metric |
| 9.5 | Call trigger | Integration | Mobile |
| 9.6 | WhatsApp trigger | Integration | API |
| 9.7 | Offer label injection | Backend | Logic |
| 9.8 | Risk value display | AI/ML | Metric |
| 9.9 | Bulk campaign send | Backend | Logic |
| 9.10 | Re-engagement tracking | Analytics | Logic |
| AI / Intelligence | |||
| 9.11 | Churn probability | AI/ML | Model |
| 9.12 | Re-entry incentive opt | AI/ML | Logic |
| 9.13 | LTV prediction | AI/ML | Model |
| 9.14 | Conversion uplift | AI/ML | Model |
10. Autopilot Campaign Engine
Total: 13 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Core Functional | |||
| 10.1 | Trigger listing | Frontend | UI |
| 10.2 | Trigger activation | Backend | Core |
| 10.3 | Revenue attribution | Analytics | Logic |
| 10.4 | Campaign count | Analytics | Metric |
| 10.5 | Time saved calc | Analytics | Logic |
| 10.6 | Audit logs | Backend | Core |
| 10.7 | Multi-trigger chaining | Backend | Logic |
| 10.8 | Campaign performance | Analytics | Metric |
| AI Triggers | |||
| 10.9 | Service drop trigger | AI/ML | Logic |
| 10.10 | Idle stylist trigger | AI/ML | Logic |
| 10.11 | Dormant client trigger | AI/ML | Logic |
| 10.12 | Seasonal auto-campaign | AI/ML | Logic |
11. Platform & AI Governance
Total: 17 Use Cases
| ID | Capability | Category | Type |
|---|---|---|---|
| Platform | |||
| 11.1 | Strict Data Isolation (DB/Schema) | Backend | Arch |
| 11.2 | Vertical Templates (Salon/Fitness) | Backend | Config |
| 11.3 | API Gateway Logic | Backend | Arch |
| 11.4 | Rate Limiting (Tenant/User) | Backend | Ops |
| 11.5 | Microservices Orchestration | Backend | Arch |
| 11.6 | Developer Portal / Tokens | Frontend | Core |
| AI Governance | |||
| 11.7 | RAG / Search Endpoints | AI/ML | Arch |
| 11.8 | Guardrails for AI Nudges | AI/ML | Logic |
| 11.9 | Budgeted Automation Limits | Backend | Logic |
| 11.10 | Automated ML Retraining | MLOps | Pipe |
| Multi-Location & Role UIs (MVP) | |||
| 11.11 | Multi-Location Support (Franchise Tenancy) | Backend | Core |
| 11.12 | Owner UI (Dashboard, Revenue, Multi-Location View) | Frontend | Core |
| 11.13 | Manager UI (Rostering, Day-to-Day Ops, Cash Register) | Frontend | Core |
| 11.14 | Franchisor UI (Aggregate Network Performance) | Frontend | Core |
| 11.15 | Franchisee UI (Location-specific Operations) | Frontend | Core |
| 11.16 | Admin Panel (Module Enablement per Tenant) | Backend | Core |
| 11.17 | On-the-Go Service Grouping (Ad-hoc bundles) | Backend | Logic |
12. Cloud Infrastructure
Total: 8 Use Cases | Detailed Docs
| ID | Capability | Category | Type |
|---|---|---|---|
| Network & Security | |||
| 12.1 | VPC Provisioning (Public/Private Subnets) | Infra | Core |
| 12.2 | Security Group Configuration | Infra | Security |
| 12.3 | NAT Gateway Setup | Infra | Core |
| 12.4 | SSL/TLS Certificate Management | Infra | Security |
| Compute & Inference | |||
| 12.5 | EC2 Inference Cluster (GPU) | Infra | Core |
| 12.6 | Ollama/vLLM Installation | MLOps | Pipe |
| 12.7 | Auto-Scaling Group (Queue-based) | Infra | Logic |
| 12.8 | Warm Pool Configuration | Infra | Ops |
13. OPS & DevOps
Total: 12 Use Cases | Detailed Docs
| ID | Capability | Category | Type |
|---|---|---|---|
| CI/CD | |||
| 13.1 | GitHub Actions Pipeline | DevOps | Pipe |
| 13.2 | Docker Build & Push | DevOps | Pipe |
| 13.3 | Staging Deployment | DevOps | Core |
| 13.4 | Production Deployment | DevOps | Core |
| 13.5 | Database Migration (Flyway) | DevOps | Pipe |
| Monitoring & Alerting | |||
| 13.6 | Centralized Logging (CloudWatch/ELK) | Ops | Core |
| 13.7 | Application Metrics (Prometheus) | Ops | Core |
| 13.8 | Alerting Rules (PagerDuty/Slack) | Ops | Core |
| 13.9 | Uptime Monitoring | Ops | Core |
| Incident Response | |||
| 13.10 | Incident Runbook | Ops | Doc |
| 13.11 | On-Call Rotation | Ops | Process |
| 13.12 | Post-Mortem Template | Ops | Doc |
14. Non-Functional Requirements (NFR)
Total: 8 Use Cases | Detailed Docs
| ID | Capability | Category | Type |
|---|---|---|---|
| Performance | |||
| 14.1 | API Response Time < 200ms (P95) | NFR | SLA |
| 14.2 | Page Load < 3s | NFR | SLA |
| 14.3 | Load Testing (1000 concurrent) | NFR | Test |
| Security | |||
| 14.4 | OWASP Top 10 Compliance | Security | Audit |
| 14.5 | Penetration Testing | Security | Test |
| 14.6 | Data Encryption (At Rest/Transit) | Security | Core |
| Reliability | |||
| 14.7 | 99.9% Uptime SLA | NFR | SLA |
| 14.8 | Disaster Recovery Plan | Ops | Doc |
15. WhatsApp Bot
Total: 36 Use Cases | Detailed Docs
| ID | Capability | Category | Type | Phase |
|---|---|---|---|---|
| Onboarding (UC-BOT-001 to 004) | ||||
| UC-BOT-001 | Chat-Based Onboarding | Backend | Core | MVP |
| UC-BOT-002 | Zero-Install Signup | Integration | Core | MVP |
| UC-BOT-003 | Preference Learning | Backend | Logic | MVP |
| UC-BOT-004 | Digital Asset Delivery | Integration | Core | P2 |
| Commerce Core (UC-BOT-010 to 017) | ||||
| UC-BOT-010 | Catalog Browsing | Backend | Core | MVP |
| UC-BOT-011 | Cart Management | Backend | Core | MVP |
| UC-BOT-012 | Slot Selection | Backend | Core | MVP |
| UC-BOT-013 | Slot Hold / Lock | Backend | Logic | MVP |
| UC-BOT-014 | Stylist Assignment | Backend | Logic | MVP |
| UC-BOT-015 | In-Chat Payments | Integration | API | MVP |
| UC-BOT-016 | Booking Confirmation | Integration | Core | MVP |
| UC-BOT-017 | Appointment Backend | Backend | Core | MVP |
| Drop-off Reduction (UC-BOT-020 to 023) | ||||
| UC-BOT-020 | Multi-Service Booking | Backend | Logic | P2 |
| UC-BOT-021 | Reschedule / Cancel | Backend | Core | MVP |
| UC-BOT-022 | Fallback Flow | Backend | Logic | P2 |
| UC-BOT-023 | Language Support | AI/ML | NLP | P2 |
| Growth & Intelligence (UC-BOT-030 to 033) | ||||
| UC-BOT-030 | Offers & Discounts | Backend | Logic | P2 |
| UC-BOT-031 | Customer Segmentation | AI/ML | Model | P2 |
| UC-BOT-032 | Analytics Dashboard | Analytics | Viz | P2 |
| UC-BOT-033 | Web Booking Bridge | Frontend | Core | P2 |
| Engagement & Retention (UC-BOT-040 to 044) | ||||
| UC-BOT-040 | Abandoned Booking Recovery | Backend | Logic | MVP |
| UC-BOT-041 | Personalized Offers | AI/ML | Logic | P2 |
| UC-BOT-042 | Dynamic Promotions Broadcast | Integration | API | P2 |
| UC-BOT-043 | Lead Capture & Qualification | Backend | Logic | MVP |
| UC-BOT-044 | Delivery/Status Updates | Integration | Core | MVP |
| Platform & Operations (UC-BOT-050 to 054) | ||||
| UC-BOT-050 | Conversation Analytics & Drop-off | Analytics | Metric | MVP |
| UC-BOT-051 | Session State & Resume | Backend | Core | MVP |
| UC-BOT-052 | Business Rules Engine | Backend | Logic | P2 |
| UC-BOT-053 | SLA Monitoring | Ops | Core | MVP |
| UC-BOT-054 | Consent, Audit & Compliance | Backend | Security | MVP |
| NLP & Safety (UC-BOT-060 to 068) | ||||
| UC-BOT-060 | Intent & Handoff (Parent) | AI/ML | NLP | MVP |
| UC-BOT-061 | Booking Intent Classification | AI/ML | NLP | MVP |
| UC-BOT-062 | Support Intent Classification | AI/ML | NLP | MVP |
| UC-BOT-063 | Feedback Intent Classification | AI/ML | NLP | P2 |
| UC-BOT-064 | Audio/Voice Processing | AI/ML | NLP | MVP |
| UC-BOT-065 | Sentiment Analysis | AI/ML | Model | P2 |
| UC-BOT-066 | Human Handoff | Backend | Logic | MVP |
| UC-BOT-067 | Language Detection | AI/ML | NLP | P2 |
| UC-BOT-068 | Fallback Handling | AI/ML | Logic | MVP |
16. AI/ML Pipelines
Total: 20 Use Cases | Detailed Docs
| ID | Capability | Category | Type |
|---|---|---|---|
| MVP: Slot & Nudge AI | |||
| 16.1 | Slot Gap Detection | AI/ML | Rule |
| 16.2 | Smart Rebalancing Suggestion | AI/ML | Logic |
| 16.3 | Processing Time Awareness | AI/ML | Logic |
| 16.4 | Empty Chair Rescue Alert | AI/ML | Logic |
| 16.5 | Re-booking Prompt | AI/ML | Logic |
| 16.6 | Upsell Suggestion | AI/ML | Logic |
| 16.7 | WhatsApp Intent Extraction | AI/ML | NLP |
| 16.8 | Sentiment Detection (Basic) | AI/ML | NLP |
| 16.9 | FAQ Auto-Response | AI/ML | NLP |
| Phase 2: Marketing Intelligence | |||
| 16.10 | Campaign Summarization | AI/ML | GenAI |
| 16.11 | A/B Test Analysis | AI/ML | Analytics |
| 16.12 | RFM Clustering | AI/ML | Model |
| 16.13 | Lookalike Audiences | AI/ML | Model |
| 16.14 | Churn Prediction | AI/ML | Model |
| 16.15 | Upsell Propensity | AI/ML | Model |
| Phase 4: Vision AI (Deferred) | |||
| 16.16 | Face Shape Analysis | AI/ML | Vision |
| 16.17 | Hair Condition Grading | AI/ML | Vision |
| 16.18 | Inventory Scanning | AI/ML | Vision |
| Governance | |||
| 16.19 | Guardrails for AI Nudges | AI/ML | Safety |
| 16.20 | Automated ML Retraining | MLOps | Pipe |
| AI Nudges Details (MVP) | |||
| 16.21 | AI Nudge Catalog & Configuration | Backend | Core |
| 16.22 | Nudge Performance Tracking | Analytics | Metric |
| 16.23 | Nudge A/B Testing Framework | AI/ML | Logic |
Summary & Cross-Reference
| Section | Use Cases | Link |
|---|---|---|
| 1. Appointments Calendar | 44 | Front Desk |
| 2. Marketing - Message Gen | 23 | Marketing Studio |
| 3. Marketing - Image Gen | 17 | Marketing Studio |
| 4. Staff - Leave | 19 | Front Desk |
| 5. Staff - Attendance | 22 | Front Desk |
| 6. Revenue Dashboard | 25 | Owner Dashboard |
| 7. Empty Chair Rescue | 13 | Marketing Studio |
| 8. AI Call Recs | 12 | Marketing Studio |
| 9. Customer Goldmine | 14 | Marketing Studio |
| 10. Autopilot Engine | 13 | Marketing Studio |
| 11. Platform & Governance | 17 | Core Platform |
| 12. Cloud Infrastructure | 8 | Cloud Infra |
| 13. OPS & DevOps | 12 | OPS |
| 14. NFR | 8 | NFR |
| 15. WhatsApp Bot | 36 | WhatsApp Bot |
| 16. AI/ML Pipelines | 23 | AI/ML |
| 17. Customer Interface | 11 | Customer Interface |
| 18. Finance & Inventory | 40 | Finance |
| 19. Analytics (Extended) | 30 | Analytics |
| TOTAL | 400+ UCs |
MVP Effort Summary (93 Use Cases)
Adjustment Applied: Simple tasks reduced by 15%, Medium by 10%, Complex unchanged.
| Module | MVP UCs | Original | Adjusted | Reduction |
|---|---|---|---|---|
| Core Platform | 15 | 180 | 162 | -10% |
| Customer Interface | 9 | 96 | 82 | -15% |
| Front Desk (Appointments) | 20 | 184 | 166 | -10% |
| Front Desk (Staff Leave) | 10 | 80 | 68 | -15% |
| Front Desk (Attendance) | 8 | 72 | 61 | -15% |
| Marketing Studio | 6 | 64 | 58 | -10% |
| Finance & POS | 9 | 108 | 97 | -10% |
| AI Layer (Nudges) | 12 | 240 | 240 | 0% |
| WhatsApp Bot | 20 | 320 | 320 | 0% |
| Analytics Dashboard | 4 | 48 | 43 | -10% |
| Owner Dashboard | 1 | 16 | 14 | -10% |
| Cloud Infrastructure | 6 | 96 | 96 | 0% |
| DevOps & OPS | 8 | 80 | 72 | -10% |
| NFR (Non-Functional) | 5 | 60 | 54 | -10% |
| TOTAL MVP | 93 | 1,644 | 1,433 hrs | -13% |
Effort Assumptions
| Item | Value |
|---|---|
| Dev Hours/Day | 6 productive hours |
| Sprint Duration | 2 weeks (60 dev-hours) |
| Team Composition | Full-stack + Backend + AI/ML |
| Buffer | 15% for testing, bug fixes |
| Total with Buffer | ~1,648 hrs |
| Estimated Sprints | ~27 sprints (single dev) |
Note: Man-hour estimates are for development effort only. Does not include: - Project management overhead - UI/UX design time - Third-party API costs (Razorpay, WhatsApp Business - to be provided by X-tics) - Infrastructure provisioning time