AWS Launches Agentic AI Service to Speed Enterprise Workload Migration by 4x
AWS Transform is now generally available, helping enterprises accelerate cloud migration and modernization projects using AI agents for VMware, mainframe, and .NET workloads.
Amazon Web Services (AWS) has launched AWS Transform, a new agentic AI service designed to accelerate enterprise workload migration and modernization by up to 4x faster than traditional methods. The service, now generally available, targets VMware, mainframe, and .NET workloads, addressing the bottleneck in cloud transformation projects that typically take 18+ months.
Key Features:
- .NET Modernization: Ports Windows-based .NET applications to Linux, reducing licensing costs by 40% and cutting 70% of modernization effort
- Mainframe Transformation: Decomposes COBOL applications into cloud-ready components in minutes instead of months
- VMware Automation: Converts on-premises VMware configurations to AWS equivalents 80x faster than manual approaches
"By using AWS Transform for .NET... we reduced 70% of the modernization effort, with 100% success." — Enrique Zazueta, Grupo Tress Internacional
How It Works:
The service uses:
- Specialized AI agents with chat interfaces
- Graph Neural Networks for dependency analysis
- Automated code transformation and testing
- Unified web dashboard for team collaboration
Customer Impact:
- Nomura Research Institute cut mainframe analysis time from 1 month to 1 week
- SourceFuse reported 90% faster execution and 80% less manual effort in VMware migrations
See Demos and Technical Deep Dive in AWS Transform for .NET Blog Post >>
AWS emphasizes this as the start of applying agentic AI to complex migrations, with plans to expand capabilities. Enterprises can access the service through AWS partners or directly via the AWS Transform console.
Related News
Lenovo Wins Frost Sullivan 2025 Asia-Pacific AI Services Leadership Award
Lenovo earns Frost Sullivan's 2025 Asia-Pacific AI Services Customer Value Leadership Recognition for its value-driven innovation and real-world AI impact.
Baidu Wenku GenFlow 2.0 Revolutionizes AI Agents with Multi-Agent Architecture
Baidu Wenku's GenFlow 2.0 introduces a multi-agent system for parallel task processing, integrating with Cangzhou OS to enhance efficiency and redefine AI workflows.
About the Author
Dr. Sarah Chen
AI Research Expert
A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.