MyRetireScore: AI-Powered Retirement Planning Platform
Haris Muneer
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Posted Feb 5, 2026
Developed MyRetireScore, an AI-driven platform for retirement planning and advisor lead management.
MyRetireScore - AI-Powered Retirement Planning Platform
Live Site: https://myretirescore.com
Project Overview
Platform: Next.js 15 (App Router)
Type: Dual-Sided SaaS Application
Purpose: AI-driven retirement assessment platform connecting consumers with financial advisors through intelligent scoring and lead management
Challenge
Build a dual-sided platform that guides consumers through AI-powered retirement assessments using Monte Carlo simulations while providing advisors with efficient lead management, real-time analytics, and full regulatory compliance.
Solution Architecture
Consumer Flow
AI Chatbot Assessment:
Conversational interface collects financial data (age, income, savings, retirement goals)
Dynamic question flow adapts based on user responses
Contextual help: chatbot suggests best answers based on user situation
Progress tracking with session recovery
Monte Carlo Simulation:
Runs 10,000+ scenarios testing retirement plan viability
Analyzes market volatility, inflation, life expectancy, withdrawal rates
Generates personalized retirement "score" showing success probability
Visual dashboard with charts showing projected outcomes
Downloadable PDF report with actionable insights
Compliance:
Automated disclosure presentation and consent tracking
End-to-end data encryption
FINRA/SEC regulatory safeguards
Advisor Dashboard
Lead Management:
Incoming assessments automatically assigned to advisors (geography, specialization, workload)
Kanban pipeline: drag-and-drop status updates (New → Contacted → Qualified → Meeting → Converted)
Integrated communication: click-to-call, email, SMS from platform
Complete lead history timeline and activity logs
Real-Time Analytics:
Live conversion metrics and response times
Campaign performance tracking (ROI by source)
Revenue projections from pipeline
Individual and team performance comparisons
Admin Panel
Team & Lead Distribution:
Manage advisor accounts, permissions, territories
Configure assignment rules (round-robin, geographic, skill-based)
Manual override and reassignment capabilities
Campaign Management:
Create and track marketing campaigns
Link campaigns to assessment landing pages
Monitor lead source effectiveness and attribution
Next.js 15 Implementation
App Router Architecture
Server Components:
Dashboard layouts, analytics tables, static content render server-side
Reduces client bundle by 40%, improves SEO
Client Components:
AI chat with streaming responses
Interactive charts (Chart.js, Recharts)
Real-time form validation
Server Actions:
Form submissions and data mutations
Monte Carlo simulation triggers
Lead assignment logic
Parallel Routes:
Advisor dashboard shows lead list + detail panel simultaneously
Improves perceived performance through concurrent loading
AI Chat & Streaming
SSE (Server-Sent Events): Questions stream word-by-word for natural conversation
State Management: React Context + local storage for session persistence
Validation: Zod schemas for type-safe financial inputs
Accessibility: Full keyboard navigation, ARIA labels, screen reader support
Monte Carlo Engine
Background Processing: Serverless functions handle 10,000+ simulations
WebSocket Updates: Real-time progress during calculation
Result Caching: Similar profiles cached, reducing compute by 60%
Visualization: D3.js renders probability curves and success rates
CRM & Analytics
Kanban Board: Drag-and-drop pipeline with optimistic updates
Real-Time Sync: Pusher WebSockets for live dashboard metrics
Assignment Engine: Geographic routing, skill-based matching, round-robin distribution
Communication: Twilio (SMS/voice), SendGrid (email) integrations
Performance & Security
Optimizations:
Code splitting: 55% smaller initial bundle
Image optimization: Next/Image with lazy loading
ISR (Incremental Static Regeneration): Dashboard updates every 60s
Redis caching: Frequent queries cached
Security:
JWT authentication with refresh tokens
RBAC (Role-Based Access Control)
End-to-end encryption for financial data
Audit logs for compliance
Key Results
User Engagement:
78% assessment completion rate (vs 45% industry average)
8-minute average completion time
4.6/5 user satisfaction score
Advisor Efficiency:
40% reduction in lead qualification time
35% increase in leads contacted per day
25% improvement in conversion rate
Platform Performance:
<1 second Monte Carlo simulation results
1.2s average page load time
99.9% uptime
Business Impact:
150% increase in qualified leads
$2.3M in projected advisory revenue
89% advisor adoption rate
Tech Stack
Frontend:
Next.js 15 (App Router, Server Components, Server Actions)
React 18, TypeScript, Tailwind CSS
Chart.js, D3.js for visualizations
Backend:
Next.js API Routes (serverless)
PostgreSQL, Redis cache
Custom Monte Carlo engine
Integrations:
OpenAI API (conversational AI)
Twilio (SMS/voice), SendGrid (email)
Pusher (WebSocket updates)
Vercel (hosting), AWS S3 (storage)
Key Takeaways
What Worked Well:
Next.js 15 Server Components: Reduced bundle size while maintaining interactivity
AI Chat Interface: Boosted completion rates significantly over traditional forms
Monte Carlo Caching: Made complex simulations feel instant (<1s)
Real-Time WebSockets: Kept advisors engaged with live updates
Next.js 15 Advantages:
Server Actions simplified form handling and mutations
App Router made complex dual-sided architecture intuitive
Built-in optimization handled images, fonts, code splitting automatically
Parallel routes improved dashboard perceived performance
Conclusion
MyRetireScore demonstrates how Next.js 15 enables building sophisticated dual-sided platforms that balance user experience with technical complexity. The AI-powered assessment makes retirement planning accessible, while the advisor dashboard streamlines lead management and conversion.
By leveraging Server Components, Server Actions, and intelligent caching, the platform delivers fast, secure, compliant financial services—connecting consumers with advisors effectively while providing scientifically-backed retirement projections through Monte Carlo analysis.