Application Transformation Management | Tech Mahindra

Transforming Applications with Intelligence

The manufacturing industry is undergoing a period of accelerated transformation, driven by the convergence of IT and OT under the influence of Industry 4.0.

At the same time, sustainability regulations are pushing enterprises to improve transparency and operational efficiency across the value chain. Advancements in AI have enabled practical applications in areas such as predictive maintenance, supply chain optimization, and quality assurance.

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The manufacturing industry is undergoing a period of accelerated transformation, driven by the convergence of IT and OT under the influence of Industry 4.0.

At the same time, sustainability regulations are pushing enterprises to improve transparency and operational efficiency across the value chain. Advancements in AI have enabled practical applications in areas such as predictive maintenance, supply chain optimization, and quality assurance.

Meanwhile, geopolitical disruptions and supply chain shocks are reinforcing the need for greater resilience and agility. Application transfer management (ATM) is purpose-built to help manufacturing enterprises navigate these challenges with intelligence and speed.

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Challenges in Manufacturing

  • Technical debt: Decades of layered, monolithic code and complex dependencies make applications costly to maintain and hard to modernize.
  • AI blockers: Outdated architecture lacks the modularity and data pipelines needed to enable machine learning and automation.
  • Disconnected systems: Shop floor, supply chain, and ERP platforms often run in isolation, limiting visibility and efficiency.
  • Slow innovation cycles: Manual development, testing, and release processes delay time-to-market and agility.
  • Talent gap: Developers and engineers struggle to keep pace with rapidly evolving technologies and AI-driven practices.
  • Change management challenges: Resistance to adopting new tools and AI– enabled workflows slows digital transformation.
  • Limited partner collaboration: A lack of co-innovation reduces access to advanced tools, solutions, and industry expertise.
  • Fragmented vendor landscape: Managing multiple providers without a cohesive strategy introduces integration and governance complexity.

Our Approach

Modernization is not just about moving applications to the cloud, it’s about enabling AI-ready, domain-relevant, partner-powered ecosystems for manufacturers.

Our approach is built on four principles:

  • Start with business goals: align every transformation to measurable outcomes.
  • Leverage domain expertise: focus on the realities of shop floor, supply chain, and engineering operations.
  • Modernize with AI in mind: ensure applications, processes, and developer tools are AI-ready.
  • Co-create with partners: accelerate scale faster through ecosystem collaboration.

Key Pillars of ATM

Application Transformation

Cloud-native, AI-ready architectures, modular microservices and APIs, real-time data pipelines for predictive insights.

Manufacturing Transformation

Domain-specific AI for shop floor, maintenance, and quality; digital twins; supply chain risk detection and dynamic logistics.

AI for Developer Productivity

AI copilots for coding, testing, documentation; automation to enhance team efficiency; generative AI for rapid prototyping.

Partner Ecosystem Collaboration

Sell-with and sell-through motions; co-creation with industry partners; integrate best-of-breed tools.

Our Differentiators

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  • Manufacturing DNA: Decades of experience across automotive, aerospace, and industrials sectors
  • Dual lens approach: Strategic (portfolio, processes, cost) and technical (modernization, cloud, automation)
  • Partner ecosystem: CAST, vFunction, Apptio, AWS, Azure, Google Cloud, NVIDIA — delivering tailored AI solutions at scale
  • End-to-End Execution: From advisory and pilot program to full-scale deployment, powered by our ATM framework

Powering Manufacturing with ATM

Examples of domain-driven solutions that demonstrate ATM in action:

Smart Factory and Production Optimization

Automating shop floor processes with closed-loop feedback and dynamic scheduling.

Intelligent Supply Chain

Real-time supplier monitoring and AI-driven logistics orchestration.

Product and Engineering Innovation

Using generative AI for accelerated design and digital twins for advanced simulation

Workforce Empowerment

Equipping operators with AI copilots and augmented reality (AR)-guided assembly and maintenance

Sustainable Manufacturing

Optimizing energy usage and enabling circular economy practices with AI

Driving Business Benefits

By adopting ATM, manufacturers achieve outcomes that go beyond technological upgrades:

  • Operational agility: Ability to adapt production in real-time, reducing downtime and improving throughput.
  • Supply chain resilience: Stronger visibility and faster responses to disruptions, lowering costs and risks.
  • Accelerated innovation: Shorter product development cycles and more efficient R&D pipelines
  • Empowered workforce: Higher productivity, improved safety and reduced training overhead.
  • Sustainability impact: Lower energy consumption and measurable progress toward carbon reduction goals

Thought Leadership

Views

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