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Predict churn earlier. Retain more customers with confidence.

Predict

Retain

Confident

ChurnLens is an explainable customer churn prediction platform that helps organisations identify at-risk customers, understand churn drivers, and take earlier retention action through business-ready analytics.

// Process

How We Make It Real

// Why Us

Take a Look on our features

Campaign-ready export

Export actionable lists for CRM and retention workflows.

Business-friendly interface

Support both technical and non-technical users.

Scalable across industries

Apply the same approach across telecom, banking, SaaS, insurance, and more.

Predic – Retain – Customers

// Team

Meet Our Team

Manish Perera
Manish Perera
Founder / Product Developer
Ajeevan Sivanandhan
Ajeevan Sivanandhan
Project Supervisor
// Demo video

// Testimonials

What Industry Experts Say

Mr. Nandana Amunuthuduwa
Mr. Nandana AmunuthuduwaCommercial Director, INSEE Cement
In my capacity as a Director of one of Sri Lanka’s leading cement, concrete, and building materials manufacturing companies, I have had the opportunity to review your concept and technical approach presented in this project. The platform demonstrates a thoughtful application of modern data analytics and machine learning techniques to address a critical business challenge for customer churn identification and proactive retention management.
Mr. Sachintha Perera
Mr. Sachintha PereraFormer Business Analyst, Riskonnect Asia-Pacific (Camms Technologies)
From the overview you previously presented, the idea behind ChurnLens appears both practical and timely. Customer retention has become a critical focus area for many organisations, particularly in industries where long-term customer relationships and subscription based services are central to business success. A system designed to proactively identify customers with a higher likelihood of churn can provide meaningful value to organisations by enabling earlier intervention and more targeted engagement strategies.
Mrs. Sakunthala Ekanayake
Mrs. Sakunthala EkanayakeManager, Information Technology, Ceylon Petroleum Storage Terminals Limited
I have reviewed your project presentation for ChurnLens, and I want to congratulate you on delivering a very strong, technically sound solution. From an IT and software engineering perspective, your work shows a high level of maturity in bridging the gap between data science and functional application development. The ChurnLens platform is an excellent piece of work. You have successfully demonstrated how to take a complex problem (customer churn) and solve it using a modern, scalable, and explainable technology stack. Keep up the great work. this is a strong addition to your professional portfolio.
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