Real challenges. Practical solutions. Measurable impact.
For a global offshore energy client specializing in mooring systems and FPSO solutions for deepwater operators worldwide, Devahuthi took end-to-end ownership of a comprehensive data and application upgrade, successfully migrating highly customized environments from legacy on-premise infrastructure to secure AWS Cloud landscapes.
The team executed a rigorous pre-migration discovery roadmap to identify and map complex environment interdependencies, and delivered robust user enablement training targeting the new 2024x features.
Built on a core technology stack of Dassault Systèmes 3DEXPERIENCE 2024x, Apache Tomee, and AWS Cloud architecture, the upgrade was delivered on time in 6 months, on budget, with zero major post-go-live issues.
For a global automotive technology client specializing in turbochargers and advanced propulsion systems, Devahuthi addressed an aging ENOVIA 2013x installation that was severely limiting system scalability and multi-CAD enterprise integration, with fragmented engineering data siloed across globally distributed teams and highly manual, error-prone change execution pipelines that put deeply linked legacy data and historic revisions at risk.
The migration delivered fully automated governance logic to optimize ECM routing, a centralized enterprise repository with secure role-based access controls, and full regulatory QMS compliance and audit readiness, with 100% of data successfully transitioned into modern Windchill environments with complete history preserved.
The result was a 60% reduction in manual change activities, as automated Engineering Change Management workflows eliminated redundant, error-prone manual tasks.
For a global energy infrastructure client in the power generation architecture space, Devahuthi designed a hybrid tiered migration strategy combining a big-bang cutover with continuous post-batch loading: active core components and the last five rolling years of product lifecycle history migrated synchronously during a compact weekend cutover window, while legacy datasets flowed iteratively post-go-live through controlled background batches.
The four-stage framework moved through read-only, safely limited access to source systems (Source), rapid metadata extraction and document vault copying (Extract), staging, profiling, deep data cleansing and schema mapping (Transform), and secure TCXML parsing with native CAD connector validation (Load).
This approach significantly compressed production cutover timelines, got engineering users operational on day one with their high-priority active product structures, and preserved historic compliance registries in staging without risking or delaying the main system cutover.
Modernize legacy applications using cloud-ready architecture, APIs and full-stack engineering.