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Centralized Messaging Platform (CMP) platform provides a complete messaging solution, which
can directly engage proprietary programs and put them in contact with
customers via a variety of engagement platforms. It is the new cloud-based, wide-scaling
platform for message delivery from CMP. The CMP supports SMTP, SMS and 2way Messaging
system. Also has integration to Apple chat and Facebook. Major advantage is the response speed and the quantum of call volumes that are now being handled. Our team is involved in:

  • Analysis of CMP on how to provide a seamless and performance effective solution

  • Design 2way messaging system support and providing automated communications to the end users.

  • Develop platform to communicate (Email and Text) to users with different templates based on events

  • Ensure successful implementation including integration to Apple chat and Facebook.

  • Leveraging AWS cloud services like Lmabda, Docker, Dynamo DB , S3 etc in order to get robust and scalable functionality.

  • Design & Develop core WEB API, MVC, Microservices using C# and Angular and AWS frameworks.


The project provides a 360-degree view of the customer. There are numerous transaction systems that get interfaced as part of customer’s lifecycle. The C360 platform integrates data elements from various transaction systems and leverages enterprise data lake to provide a holistic view of customers to enterprise using Unica.

Amazon Redshift is used as the primary data store. Data generated from transaction source systems will flow through the data pipeline from RDZ (raw data zone), to EDZ (enterprise data zone), to the C360 data zone (Redshift), which is classified as BDZ (business data zone).

The project aims to integrate various data feeds to enterprise data lake, laid on Amazon EC2 cluster with Hortonworks Hadoop distribution. The legacy Data warehouse is slated for de-commissioning once the data feeds are completely switched to data lake.

Data lake is classified as RDZ (raw data zone) built on HDFS, and EDZ (enterprise data zone) built on Hive, for storing the raw and transformed data respectively.  The data transformations from RDZ to EDZ are implemented in Scala programming language which runs on spark computing framework.

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