update
Jun 1, 2026
By Teun
Clearscale says AWS Transform cuts migration timelines up to 80%
Clearscale says it is using AWS Transform, Amazon’s agentic AI migration service, to speed enterprise modernization for VMware, .NET, and mainframe workloads. The company says its Clearview Migration Methodology can reduce migration time by up to 80% and helped one global enterprise cut a 14-month VMware program to under six months.
Clearscale says it is using AWS Transform, Amazon’s agentic AI service for enterprise modernization, to shorten migration projects that often take months or years. The company says its Clearview Migration Methodology helps organizations automate parts of VMware, .NET, and mainframe migrations and reduce execution time by up to 80%.
AWS Transform, or ATX, is designed to handle the most manual parts of cloud migration, according to Amazon and Clearscale. Those tasks include discovery, dependency mapping, migration sequencing, network reconfiguration, and validation after systems move.
⚡ New to this?
This story is about using AI to speed up cloud migrations, which are the projects companies run when they move old systems from legacy servers to cloud platforms like AWS. An agentic AI service is a system that can carry out multi-step tasks with some independence, instead of just answering questions.
The news matters because modernization projects often stall on manual work like finding dependencies between apps, planning migration waves, and checking whether systems still work after the move. If the claims hold up, this could reduce time, cost, and risk for large companies with VMware, .NET, or mainframe systems.
🦞 OpenClaw angle
If you run self-hosted automation or migration tooling, treat this as a reminder to separate repeatable migration tasks from human approval steps. Build agents that can do discovery, dependency mapping, and validation reports, but keep network changes, rollback triggers, and production cutovers behind explicit gates.
For OpenClaw workflows, add structured outputs for inventory, wave plans, and post-migration checks so downstream automation can use them directly. If you manage legacy app portfolios, standardize your runbooks now so an AI agent can operate on them later without guessing.
In Clearscale’s view, those are exactly the steps that slow down large modernization programs. The company said application complexity is a major reason timelines slip, especially when teams have to work through legacy estates made up of VMware environments, older .NET frameworks, or customized mainframe systems.
Clearscale said the longer organizations stay on those systems, the more technical debt and licensing exposure they accumulate. The company also said delayed migrations can slow access to AI features that competitors are already using.
The company described AWS Transform as “the first agentic AI service purpose-built for large-scale modernization of legacy environments.” In practical terms, that means the service uses AI agents to help automate repetitive migration work rather than leaving most of it to manual engineering effort.
For VMware migrations, AWS Transform orchestrates the migration lifecycle, including discovery, dependency mapping, wave planning, network configuration, and server migration, according to Clearscale. The company said teams can query the agent in real time while migration work is in progress.
Clearscale also said AWS Transform accelerates full-stack Windows modernization, including .NET and SQL Server, by up to 5x. The company said the service can cut operating costs by up to 70% by removing costly licenses.
For mainframe workloads, Clearscale said AWS Transform can help with AI-driven refactoring of monolithic codebases. That is meant to support modernization on AWS without the long manual rewrites that have made many mainframe programs expensive and slow.
The company also pointed to AWS Transform Custom, which it said can automate upgrades for APIs, frameworks, and custom code. Clearscale said that version updates, framework migrations, performance tuning, and code analysis can be improved over time as the service is used in more engagements.
Clearscale’s main selling point is not the tool alone, but how it packages the tool for enterprise programs. The company said it configures custom Transform agents for a customer’s application field and integrates AWS Transform into an AI-native SDLC, or software development lifecycle.
Through the Clearview Migration Methodology, Clearscale said it wraps modernization work in governance, dependency modeling, landing zone and security architecture alignment, migration wave orchestration, deployment readiness checks, rollback planning, and post-migration optimization. The company said that structure is intended to reduce risk while speeding delivery.
Clearscale said this approach has already shortened one VMware project. In a case study, the company said a global enterprise’s projected 14-month migration was completed in under six months, saving millions in projected licensing overhead and freeing engineering teams to focus on other work.
The company is positioning the approach as a way to move larger application portfolios faster without giving up oversight, security, or stability. Clearscale said organizations can schedule a complimentary AWS Transform assessment to map out a migration roadmap.
