
- Category:Compliance Automation / Data Security
- Stack:Next.js, Node.js, TypeScript, Python, Redis, PostgreSQL, AWS, Docker, Web Security APIs, Encryption Services
- Client:Kedexa (Internal Compliance Automation System)
- Region:Global
- Completed:Q2 2024
A professional-grade DNC (Do Not Call) scrubbing and compliance verification system that validates phone databases against global regulatory lists in real time with high-speed processing and enterprise-level privacy protection.
01 The Challenge
Businesses handling large-scale outbound communication faced serious compliance risks when contacting numbers listed on Do Not Call (DNC) registries. Manual verification processes were slow, error-prone, and unable to scale with high-volume datasets. This led to potential legal penalties, wasted outreach efforts, and damaged brand reputation due to non-compliant calling practices. Kedexa needed a system capable of real-time verification, bulk file processing, and guaranteed regulatory alignment with global DNC standards.
02 The Solution
We developed FreeDNC Scrubber, a professional-grade compliance verification platform designed for high-speed validation of phone numbers against national and global Do Not Call registries. The system supports both bulk file uploads and single-number verification with ultra-low latency checks. Phone numbers are instantly cross-referenced with updated compliance databases to ensure regulatory adherence before any outreach activity. A secure access portal was implemented with user authentication, role-based access, and encrypted processing pipelines. The backend architecture was optimized for large-scale processing, enabling millions of records to be scrubbed efficiently. The platform also includes an intelligence dashboard showing compliance status, verification logs, system health, and regulatory risk insights, helping businesses maintain full transparency and audit readiness.
Results After Launch
- Reduced compliance risk across outbound campaigns
- Enabled real-time DNC verification for large datasets
- Improved data accuracy before customer outreach
- Prevented potential regulatory fines and violations
- Processed millions of records with high-speed matching
- Strengthened data privacy and encryption standards
- Improved operational efficiency for sales and support teams
- Delivered scalable infrastructure for enterprise usage

