SiNGL

What is SiNGL?

SiNGL is an AI-powered master data management (MDM) platform designed to unify, govern, and activate trusted customer and enterprise data. It leverages advanced algorithms and machine learning to deduplicate records, scoring each record to determine whether two records belong to the same physical entity based on configurable thresholds. This enables organizations to maintain a single, accurate view of their data across systems.

Key features include rapid deployment in under 90 days, support for both on-premise and cloud environments, and the ability to train the model with your own enterprise data. SiNGL delivers direct and indirect benefits across revenue growth, cost optimization, and operational efficiency. For revenue growth, it improves up-sell and cross-sell opportunities by analyzing household relationships and life events, enhances marketing effectiveness with hyper-personalization, and increases campaign yield rates. It also helps identify cross-selling opportunities arising from M&A activity.

For cost optimization, SiNGL eliminates redundant calls and improves first-call resolution, reduces duplicated campaign mailing and printing costs, lowers IT application development and maintenance costs through service-oriented architecture (SOA), and minimizes data storage costs. It also reduces fraud risk and errors in billing, statements, and payments by ensuring data accuracy.

Operational efficiency gains include a more seamless customer experience across channels, improved claims processing, streamlined onboarding and new account setup, better customer retention, and enhanced trust in reporting and BI systems. SiNGL reduces the effort required to integrate new systems during M&A and to implement new programs and initiatives.

Use cases span customer onboarding, 360-degree view including house-holding, regulatory compliance (DPDP, GDPR, KYC, AML), and quick integration of new systems. Technical details: SiNGL uses advanced scoring algorithms with configurable thresholds, supports on-premise and cloud deployment, and can be trained on enterprise-specific data. It is designed for scalability and rapid time-to-value, making it suitable for organizations of all sizes seeking to master their data.

Use Cases

Key Features

AI powered deduplication record scoring rapid deployment under 90 days on premise and cloud support train with enterprise data household relationship analysis hyper personalization campaign yield improvement M&A cross sell identification redundant call elimination

Who is it for?

data governance teams, marketing departments, IT managers, enterprise data architects, customer experience teams, revenue operations teams

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