Cloud computing has transformed enterprise operations by enabling the migration of applications from costly data centres to modern platforms, leveraging microservices, containers, and serverless architectures for cost efficiency and agility. This shift allowed businesses to adapt and thrive in a rapidly evolving digital landscape. However, as organizations migrate to Cloud, they encounter new challenges such as escalating costs, ensuring compliance across multi-cloud environments, mitigating security risks, optimizing performance, and monitoring complexities.
In late 2025, the focus has moved beyond simply migrating workloads in the cloud, but also to optimise it on Cloud. To do so, the competitive advantage now lies in making applications intelligent through AI integration. Enterprises are entering an AI-first era, where success depends on embedding AI into processes for automation, prediction, and personalization at scale. Agentic AI—systems capable of reasoning, planning, and acting autonomously—offers a solution by combining cloud scalability with AI-driven decision-making. This approach not only addresses existing pain points but also unlocks opportunities for intelligent cloud operations, including use cases in performance optimization, security, fraud detection, and automation.
1. Cloud Native Architecture Adoption
The Challenge: AI-first architectures demand modular, scalable, and event-driven designs. Yet many organizations still operate with infra-centric, monolithic cloud-first setups, limiting agility and innovation.
AI to the Rescue:
2. Portfolio Assessment & Cloud Strategy
The Challenge: Post-migration, many enterprises lack clarity on which applications to modernize, retire, or re-architect. Without a clear roadmap, cloud investments fail to deliver optimal ROI.
AI to the Rescue:
3. Application Modernization for Monolith Legacy Systems
The Challenge: Enterprises running legacy .NET and Java applications often face scalability issues, high maintenance costs, and limited integration with modern cloud-native and AI-driven ecosystems. These monolithic systems slow down innovation and hinder real-time responsiveness.
AI to the Rescue:
4. Cloud Cost Explosion
The Challenge: As companies scale across multiple cloud regions and providers, they often face unpredictable bills. Engineering teams overprovision compute for safety, while shadow IT creates hidden workloads.
AI to the Rescue:
5. Performance Bottlenecks in Multi-Cloud Deployments
The Challenge: Enterprises running workloads across Azure, AWS, and GCP often struggle with latency, routing inefficiencies, and integration failures. Cloud-first solved availability but not real-time performance.
AI to the Rescue:
6. Complexity in Observability and Monitoring
The Challenge: Traditional monitoring tools often produce fragmented data, forcing teams to manually correlate logs, metrics, and traces across multiple platforms. This lack of unified observability leads to delayed root cause analysis, prolonged outages, and higher operational costs.
AI to the Rescue:
The Problem:
A leading airline successfully migrated its booking systems to the cloud for scalability during peak travel seasons. However, post-migration challenges persisted across multiple dimensions:
The Cloud + AI Approach:
The Outcome:
Coforge has a comprehensive prebuilt tools, accelerators and AI based services to help you in addressing challenges witnessed during post migration. It has readymade AI driven platform, tools and agents which can analyse your current system landscape and suggest recommendations to optimize your operational efficiencies and performance.
1. Coforge Forge-X AI Integrated Engineering and Delivery Platform
Coforge Forge-X is an integrated engineering and delivery platform, purpose-built on Agentic AI principles that completely transforms how software is delivered. This comprehensive platform harnesses autonomous AI agents that draw on deep engineering expertise and use contextual decision making based on the firm’s industry domain depth to deliver complex technology transformations at scale.
The Coforge Forge-X platform is anchored on three strategic pillars. Firstly, the platform embeds the firm’s deep domain expertise into its engineering fabric to ensure that engineering decisions are informed by domain semantics, tool functions with contextual awareness, and deliverables are aligned with both business and technical expectations. Secondly, the team has developed a suite of specialized AI agents that are purpose-built to address specific engineering challenges. The agents are continuously refined through real-world project feedback and are designed to deliver incremental intelligence, enhance productivity and agile optimization. And thirdly, the platform is equipped with a comprehensive suite of industrial-grade tools and accelerators that are tailored to specific engineering functions.
These tools include CodeInsightAI- a GenAI-powered tool for reverse and forward engineering, that mitigates risks associated with undocumented and fragmented systems, bridges the legacy skill gap through business and technical insights from code, and accelerates transformation through forward engineering, BlueSwan- an AI-led next-gen digital assurance & quality engineering platform, NORTHSTAR- for continuous integration and delivery for end-to-end observability and EvolveOps.AI- a next generation, autonomous IT operations management platform that delivers end-to-end autonomous operations across the entire lifecycle of your hybrid cloud resources – from design, build, analyse to autonomous resolution.
2. XJava and XNet – Coforge’s AI-Powered Modernization Accelerators
XJAVA Modernization Accelerator
XJAVA is a next-generation accelerator that speeds up the modernization of legacy Java applications. It empowers enterprises to enhance regulatory compliance, boost business agility, and fast-track their cloud transformation journeys. By intelligently analysing legacy Java applications, XJAVA automatically generates comprehensive modernization assessment reports and guides the upgrade from outdated / unsupported frameworks to modern and industry-leading technologies.
XNET Modernization Accelerator
XNET is an advanced accelerator designed to expedite the modernization of legacy .NET applications. It enables organizations to strengthen security, improve scalability, and accelerate their cloud transformation initiatives. By leveraging intelligent analysis of existing .NET systems, XNET produces detailed modernization and cloud readiness reports while guiding seamless upgrades from outdated frameworks to contemporary, high-performance platforms and latest technologies.
3. EvolveOps.AI – Enhance your Enterprise IT Operations through AI powered insights
Introducing EvolveOps.AI – a next generation, Autonomous IT Operations Management Platform that delivers end-to-end autonomous operations across the entire lifecycle of your Hybrid Cloud resources – from design, build, analyse to autonomous resolution.
Key Modules of EvolveOps.AI
By leveraging a combination of advanced AI models and machine learning techniques, the EvolveOps.AI platform effectively identifies recurring patterns, anomalies, and correlations within complex, high-dimensional datasets. A key differentiator lies in the fine-tuning of these models using customer-specific data, ensuring highly accurate predictions and insights.
The cloud-first era was about infrastructure transformation. The AI-first era focuses not only on ai driven/powered infrastructure transformation but also on ai powered business transformation & optimization. Enterprises that align cloud and AI strategies—embedding intelligence into supply chains, banking transactions, and travel experiences—will not just cut costs but unlock new business models and competitive advantages.