AI-powered churn prediction | Transform your business with real-time customer retention analytics
Industry-specific solutions for telecom and banking sectors
Specialized prediction model for telecommunications companies
Advanced CLV-based prioritization system for banking sector
High-performance FastAPI infrastructure
Advanced ML models powered by Scikit-learn
Automated notification and intervention system
Comprehensive analysis and visualization tools
Your data is protected with bank-level security infrastructure
Your data is protected with enterprise-level security protocols
Bcrypt algorithm with 95/100 security score. All passwords are salted and hashed, protected against rainbow table attacks.
JWT token-based authentication, account lockout system (15 min lock after 5 failed attempts), and email verification for secure access.
Comprehensive rate limiting, XSS/CSRF protection, SQL injection prevention - all attack vectors are secured.
Full compliance with OWASP Top 10 security standards. Regular security scans and penetration testing.
All security events are logged. Real-time anomaly detection and automated alert systems.
8 critical HTTP security headers active. Content Security Policy, XSS Protection, Frame Options and more.
Microservice-based scalable architecture
Comprehensive guides and examples
Set up the system and make your first prediction in 5 minutes
English5 dakikada sistemi kurun ve ilk tahmininizi yapın
TürkçeSaaS pricing and API access guide
EnglishSaaS fiyatlandırma ve API erişim rehberi
TürkçeAll endpoints, parameters and examples
EnglishTüm endpoint'ler, parametreler ve örnekler
TürkçeModel training, feature engineering and optimization
EnglishModel eğitimi, feature engineering ve optimizasyon
TürkçeSteps to deploy to production environment
EnglishProduction ortamına deploy etme adımları
TürkçeEasy integration with RESTful API
https://predictivs.com/api/telco
Log customer activity and predict churn risk
{
"customer_id": "CUST_12345",
"call_duration_mins": 150.5,
"data_usage_gb": 8.5,
"support_tickets_count": 2,
"contract_type": "Monthly",
"monthly_charge": 89.99
}{
"message": "Activity logged successfully",
"customer_id": "CUST_12345",
"timestamp": "2025-11-14T10:30:00.000000"
}List recent predictions
System health check
https://predictivs.com/api/banking
Log customer activity with churn and CLV analysis
{
"customer_id": "BANK_67890",
"account_age_months": 36,
"account_type": "Premium",
"num_products": 3,
"average_balance": 25000.00,
"total_transaction_count": 45,
"total_transaction_amount": 12500.00,
"credit_card_usage_ratio": 0.65,
"loan_amount": 50000.00,
"mobile_app_logins": 28,
"online_banking_usage": 15,
"atm_usage_count": 8,
"customer_service_calls": 2,
"complaint_count": 1,
"branch_visits": 2,
"age": 42,
"geography": "Urban",
"is_active_member": true
}{
"message": "Banking activity logged successfully",
"customer_id": "BANK_67890",
"timestamp": "2025-11-14T10:30:00.000000"
}Detailed analytics report
Customer detail information