2-Day Production Build

AI Success Insights Dashboard

A production-grade customer success platform built in 2 days, demonstrating transparent health scoring, AI-powered insights with GPT-5, and comprehensive OWASP LLM security compliance (A- grade). Upload CSVs of usage, NPS, and support data to see portfolio health, at-risk segments, and recommended plays. Deployed on AWS Lambda + Vercel with extensive security hardening and observability.

Transparent Health Scoring
Multi-factor health model combining usage, adoption, support, and engagement metrics with explainable risk factors
AI-Powered Insights
GPT-generated executive summaries and actionable recommendations based on customer health trends and risk signals
Portfolio Analytics
Real-time portfolio health tracking, ARR-by-segment analysis, and at-risk account identification for faster QBR prep

Production-Grade Security & Infrastructure

Built with comprehensive OWASP LLM Top 10 compliance and enterprise-grade deployment practices

🔒 AI Security (A- Grade)
  • ✅ Input validation & prompt injection prevention
  • ✅ Output sanitization & XSS protection
  • ✅ Rate limiting via AWS API Gateway (10K req/sec)
  • ✅ OpenAI budget controls & usage monitoring
  • ✅ Secure model access & API key management
  • ✅ Comprehensive security documentation
☁️ Cloud Infrastructure
  • ✅ AWS Lambda + API Gateway (serverless)
  • ✅ Neon PostgreSQL (serverless, auto-scaling)
  • ✅ Vercel frontend deployment
  • ✅ CORS configuration & SSL/TLS encryption
  • ✅ Environment-based configuration
  • ✅ Production monitoring & logging
🤖 GPT-5 Integration
  • ✅ Advanced reasoning & higher accuracy
  • ✅ 45% fewer hallucinations vs GPT-4o
  • ✅ 50-80% token efficiency (cost savings)
  • ✅ Context-aware customer insights
  • ✅ Structured output validation
  • ✅ Graceful error handling & fallbacks
📋 Development Practices
  • ✅ Type-safe APIs (TypeScript + Pydantic)
  • ✅ Database migrations & schema management
  • ✅ Comprehensive API documentation
  • ✅ Git workflow & deployment automation
  • ✅ Security scanning & vulnerability checks
  • ✅ Performance optimization & caching

Case Study

How this solves real CS challenges

Problem

CS teams juggle usage data, tickets, and NPS without a shared “source of truth.” Health scores are opaque, QBR prep is manual, and it's hard to explain why an account is at risk or which actions to prioritize.

Solution

A transparent scoring model that weights adoption, support load, engagement, and NPS. AI summaries explain the “why” behind each score, and playbook recommendations surface the next-best actions. All data lives in one dashboard with drill-down views.

Outcome

Faster QBR prep with pre-generated insights, clearer renewal priorities based on data-driven health scores, and explainable health trends that build trust with stakeholders. CSMs spend less time on spreadsheets and more time with customers.

Tech Stack

Built with modern, production-ready tools

Frontend

  • • Next.js 15 (React)
  • • TypeScript
  • • Tailwind CSS + Shadcn UI
  • • Recharts for visualizations

Backend

  • • FastAPI + AWS Lambda
  • • Neon PostgreSQL (Serverless)
  • • OpenAI GPT-5 (Advanced Reasoning)
  • • Pandas + SQLModel ORM

Ready to explore?

Start by uploading your customer data or generate mock data to see the dashboard in action