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Featured Speakers

Keith GroomAWS
Keith Groom

WW Leader, Migrations & Modernization

Keith brings two decades of business development expertise and now leads AWS’s Migration & Modernization Partner COE, providing programs and solutions to speed and derisk the move to cloud.

Nits JeganathanAWS
Nits Jeganathan

Sr. Product Manager, AWS Transform

Nits brings 15 years in edge computing, system dev, and app modernization to his role leading AWS Transform for .NET, using Gen-AI to speed legacy modernization and boost UX.

Nicolas BidauxCAST
Nicolas Bidaux

Solution Design Engineer

Nicolas applies two decades of software intelligence and mapping expertise, recently teaming with AWS to embed CAST insights in AWS Transform for .NET and speed clients’ modernization.

Damien SantéCAST
Damien Santé

SVP Technology Alliances

Damien draws on a telecom-to-cloud career to lead global tech partnerships at CAST, integrating software intelligence solutions across cloud, AI, and ISV ecosystems worldwide.

Executive Summary

Modernizing Windows-based .NET estates – often impacting tens or even hundreds of applications – no longer has to be slow, repetitive, or resource-draining. What if you could automate every repeatable step, sparing expert resources for the tasks that truly need them?

In this 45min session experts from AWS and CAST show how a highly automated approach combining AWS Transform for .NET with CAST software mapping and intelligence accelerates large-scale migrations while safeguarding codebase integrity.

What you’ll see:

  • Instant roadmap creation – automatically group applications into migration waves based on their cloud maturity.
  • AI-powered code transformation – convert .NET applications to Linux up to 4× faster while trimming Windows licensing costs by ≈40 %.
  • Post-conversion validation – ensure the structural integrity of the transformed applications before going live.

Live demo & Q&A.

For transformation leaders, engineering leaders, and architects seeking to accelerate and de-risk .NET modernization at scale on AWS.