We are masters of the tried and tested process

There are huge clusters of unfiltered data that require structuring and undergo several operations prior to movement to a common pool called the data lake. Extract, Load, and Transform (ELT) is a complex process that helps build a system from a repository.

ELT processes are the most effective while adopting the pipeline automation methodology. It results in minimized operational efforts, fast and accurate refresh times and organizing of structured data into multiple readable formats.

We are masters of the tried and tested process

Our engines are in sync with the AWS cloud during data warehousing. The vast capabilities of AWS enable us to scale data management and automation by pumping several lines of code.

The end goal is to generate true business value with actionable insights while data is being processed in the final (transform) stage.

Our robust self-engineered solutions


We’ve moulded our Data Lake Platform into a scalable all-purpose system that integrates with the ecosystem of various technologies for diverse operations on data. The platform is the fountain of life that gives birth to data solutions, data models, ML models, statistical and deep learning analysis. It supports real-time data ingestion and analytics and is adored by the Business Analytics and Data Science teams.

Data Lake Platform

This doubles up as one of our best products and is powered with semantic matching algorithms. The Dedupe Engine eliminates redundancy problems, accurately searching over millions of records with sub-second latency. It finds its purpose in lead qualification, underwriting workflow, cross-sell and up-sell cycles. It’s a convenient solution that provides API driven integration for most business platforms - CRM, Policy Admin, LOS, LMS, Servicing etc.

Dedupe Engine

Customer 360 studies every single customer in depth. It learns by defining the brand touchpoints, identifying different customer parameters (demographics, transactional activity), and correlates behavioural patterns to draw conclusions. The objective is to generate a view for customers based on previous inferences to target similar customers and deliver the best customer experience available.

Customer 360

We provide a platform that enables users to consume and analyze data in real-time. It’s brought into functionality with machine learning algorithms to conduct real-time processing which supports streaming datasets from various data sources, mechanisms and endpoints at low latency. It integrates well with consumable feeds and data for synchronous or asynchronous use.

Real-time Stream Analytics Platform

You are one step closer to taking calculated decisions