AI-Powered Lead Intelligence & Smart Qualification Platform
Live Application: https://leadintelai.vercel.app/
LeadIntelAI is a production-ready AI-driven lead intelligence platform designed to help businesses capture, enrich, score, and prioritize leads using behavioral signals and machine learning insights.
The platform is engineered with scalability, modularity, and performance in mind — suitable for SaaS products, B2B sales teams, and enterprise workflows.
- Auto-enrich company & user metadata
- Role & industry inference
- Behavioral interaction tracking
- Dynamic scoring algorithms
- Intent-based weighting
- Custom scoring models per tenant
- NLP-driven sentiment analysis
- Engagement pattern recognition
- AI-generated action recommendations
- Funnel analytics
- Lead source attribution
- Conversion probability indicators
- RESTful endpoints
- Webhook-ready
- CRM integration ready
┌───────────────────────────┐
│ Client (UI) │
└───────────────┬───────────┘
│
▼
┌───────────────────────────┐
│ Next.js Frontend │
└───────────────┬───────────┘
│
▼
┌───────────────────────────┐
│ API Layer (Node.js) │
└───────────────┬───────────┘
│
┌──────────────────────┼──────────────────────┐
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ PostgreSQL │ │ Redis Cache │ │ AI Workers │
│ Lead Storage │ │ Session/Data │ │ Scoring/NLP │
└──────────────┘ └──────────────┘ └──────────────┘
| Layer | Technology |
|---|---|
| Frontend | Next.js (App Router) |
| Backend | Node.js / Express |
| Database | PostgreSQL |
| Cache | Redis |
| AI Engine | OpenAI / Custom Models |
| Deployment | Vercel |
| Auth | JWT |
/app
/api
/dashboard
/components
/hooks
/lib
/server
/controllers
/services
/models
/middlewares
/database
schema.sql
/utils
/tests
POST /api/leads
{
"name": "John Doe",
"email": "john@company.com",
"company": "TechCorp",
"source": "Landing Page"
}GET /api/leads/:id/score
Response:
{
"leadId": "abc123",
"score": 87,
"intentLevel": "High",
"recommendation": "Schedule demo immediately"
}score = (
engagement_weight * engagement_score
) + (
company_fit_weight * firmographic_score
) + (
behavior_weight * intent_score
)
Example Factors:
- Email opens
- Website revisit frequency
- Pricing page views
- Company size
- Industry match
1. Lead event captured
2. Event stored in database
3. Background worker processes interaction
4. NLP sentiment analysis performed
5. Intent probability calculated
6. Lead score updated
7. Dashboard reflects new score
- JWT-based authentication
- API rate limiting
- Input validation & sanitization
- Encrypted database connections
- Role-Based Access Control (RBAC)
git clone https://github.com/jenilrupapara001/LeadIntelAI.git
cd LeadIntelAI
npm install
Create .env file:
DATABASE_URL=your_postgres_url
REDIS_URL=your_redis_url
JWT_SECRET=your_secret
OPENAI_API_KEY=your_key
NEXT_PUBLIC_API_URL=http://localhost:3000
npm run dev
- Redis caching for frequently accessed leads
- Pagination for dashboard tables
- Optimized database indexing on email & company
- Background workers for AI tasks
- Edge deployment for low latency
- Horizontal scaling via stateless API
- Background queue processing
- Separate AI worker service
- Database read replicas (future)
- Event-driven expansion model
- CRM native integrations
- Advanced predictive churn modeling
- Automated outreach recommendations
- Multi-tenant enterprise mode
- Custom AI model training
Jenil Rupapara Full Stack Engineer | SaaS Architect | AI Systems Builder
MIT License
LeadIntelAI is designed to bridge AI intelligence with sales performance — transforming raw lead data into actionable business insights.