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XENON FRAMEWORKAccelerating data modernization and cloud migration at scale

Businesses looking to modernize and transform their data are challenged by legacy systems that cannot support data analytics at scale. They look to simplify and modernize their data ecosystem and economically scale on the cloud and hybrid modes to achieve speed-to-market and remove data bottlenecks to accelerate their digital initiatives with high levels of data security and governance.


Mphasis’ Xenon Framework offers a proven three phase execution model and Mphasis own IP/Accelerators to build a modern data platform with new age tools and advanced analytics capabilities on any cloud. Using Xenon allows our client’s to provide contextual data products that are well-aligned to business needs at optimized total cost of ownership. It provides an end-to-end solution for data migration services to the any public / hybrid Cloud by leveraging data across all lines of business, and simplifying and modernizing the data and analytics ecosystem while preserving data ownership and provenance.



  • Organizations may opt for either an ‘as-is’ migration with minimal retrofitting or transformation of data ecosystem with data migration or an optimized combination of both.
  • Through a standard three phase execution model (ASSESS, ADAPT and IMPLANT), Xenon enables large petabyte scale migration of data and data warehouse appliances.


Leveraging the best of partnerships and our IP assets, we develop a Cloud data ecosystem that can leverage the organization’s data across all lines of business to deliver:

  • Seamless, fully governed, real-time insights
  • Decision support capabilities that preserve the data ownership and provenance
  • Total compliance to regulatory requirements
  • Optimized cost of operations and reduced IT dependency


Xenon leverages the Mphasis’ SAGE (Solution Architect Group for Enterprise) Framework to address key requirements of security, availability of data, governance and execution to drive Cloud data system design and adoption. It also allows use of Mphasis accelerators to build a complete data objects repository and derive the data and process dependence and realistic data lineage. The “App-Cluster” and “Release-Plan” frameworks provide a systematic way to segregate workloads and data that can be migrated to cloud as per the lineage and dependencies. The workstreams framework allows creating dedicated execution swim-lanes for the programs to deliver the entire program in agile fashion. Also, Xenon offers a specialized “side car” approach for the parallel testing of legacy and new data systems to build end-user confidence in migrated data and workload accuracies. Depending on the client’s preference, Xenon can offer multiple hard or soft production drops to provide modern data capabilities to end-users and faster time to market.



Across the three phases of execution, we have teamed up with best-in-class partners to deliver excellence.


Amazon Web Services
Google Cloud
Microsoft Azure


Next Pathway



Mphasis’ Xenon framework effectively addresses major client’s requirements with a range of advantages:


Efficient utilization of existing resources
Xenon leverages existing tech stack and uses a ‘Lift-and-shift’ approach, wherever possible, to minimize tech debts

Effective de-risking of projects
Xenon utilizes proven frameworks such as SAGE, Application Clustering, Release Plan, Workstreams, Side-Car and leverages our own IP/Accelerators coupled with many partner products / tools / utilities to increase predictability and achieve significant de-risking of data migration programs

High scalability
Through a winning combination of technology, modernization strategies and a well-structured, 3-phase execution model, Xenon handles data volumes according to business demands, with no ceiling on data growth and no constraint on the ability to process high volumes of data workloads

Flexible and innovating pricing
Xenon offers the advantages of flexible pricing models – fixed, a la carte, or outcome-based. Through transparent cost allocation for data usage, enterprises enjoy the advantage of proportionate charges for actual usage