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AI/works™ × AWS Transform

Transform legacy systems into AI-ready operational platforms

AWS Back

Enterprise AI is blocked by the systems it depends on. Mainframes, monoliths and disconnected data estates carry decades of operational intelligence — and they were never designed for AI to read, reason over or act on.

 

Traditional modernization programs assumed organizations could wait years to realize value. AI changes those economics. Modernization is no longer just about moving infrastructure to the cloud. It is about turning legacy systems into adaptive operational platforms that continuously evolve as your business, your regulations and your AI capabilities change.

 

Start with a 3-day workshop. Continue with a 3-week assessment and proof of value. Ship your first modernized slice into production within 3 months. Fixed-price at every phase. AWS-funded entry. Available directly and on AWS Marketplace.

AI is blocked by legacy systems

Most enterprises already have the intelligence and the systems that hold it back.

Most enterprises already possess the operational intelligence required to run AI-driven products and experiences. That intelligence lives inside customer workflows, transaction systems, manufacturing operations, supply chains and decades of embedded business logic. The data is there. The rules are there. The expertise is there.

 

The problem is that those systems were never designed for AI to interact with them. Data is fragmented across silos. Business rules are buried in procedural code. Integrations are brittle. Operational context is undocumented. Even simple modernization work needs months of manual analysis before a team understands how the system actually behaves.

 

Organizations need the intelligence trapped inside legacy systems. Those same systems prevent AI from safely accessing and evolving that intelligence. Closing that gap is the work.

The joint operating model

 

A modernization operating model built for the AI era.

 

Thoughtworks and AWS combine AI/works™ and AWS Transform into a single operating model for modernization. Not a one-off migration. A repeatable engine that rationalizes the estate, enriches a reusable context library from the systems you already run, defines a roadmap, and delivers incremental transformation waves. Built to keep evolving with the business.

AWS Transform: the modernization execution engine

 

AWS's agentic AI service for large-scale migration and modernization. Handles dependency analysis, decomposition, transpilation acceleration and agentic workflow automation across the legacy estate.

AI/works™: the enterprise modernization and context layer

 

Thoughtworks' Agentic Development Platform. Builds the reusable legacy context library, enriches modernization intelligence with enterprise and industry domain context, generates governed specifications, and powers AI-assisted delivery and continuous regeneration of modernized systems.

This rationalization creates the modernization roadmap that guides incremental transformation across your enterprise.

Not every application in a legacy estate should be modernized the same way.

 

Most legacy monoliths are not single applications. They are collections of business domains, shared services, batch platforms, operational workflows and tightly coupled systems that have evolved over decades. The first job is to understand what is actually there and decide what should happen to each part of it.

 

Using AI/works™ and AWS Transform, we analyze the legacy estate to identify modernization seams, map dependencies, set priorities, and recommend the right disposition for each application and domain.

Disposition strategies we apply:

 

  • Leave the system as-is, or decommission it
  • Redeploy the application and dependencies to new infrastructure with no functional changes
  • Move the business capability to a SaaS or COTS solution
  • Make minor changes so the application runs on cloud-native technologies
  • Transform to a new language or architecture with approximate business intent
  • Refactor with validated, equivalent business intent
  • Redevelop with new technologies, architecture and a new business intent

Get a detailed breakdown of what

to expect across the three days.

Download the full agenda

Agenda for incremental modernization through recurring transformation waves

3 days

Modernization workshops and shaping

 

Align business, architecture and modernization priorities through collaborative workshops focused on:

 

  • business outcomes
  • user experience expectations
  • governance and compliance requirements
  • modernization objectives
  • operational constraints
  • AI ambitions
  • transformation risks.

 

You leave with modernization canvases, domain maps and initial modernization hypotheses.

3 weeks

Analysis, disposition, roadmap and proof of value

 

Use AI/works™ and AWS Transform to:

 

  • analyze the legacy estate
  • enrich the legacy context library
  • define disposition strategy,
  • create the modernization roadmap
  • develop proof-of-value modernization outputs

 

You leave with modernization prototypes, modernization specifications, target-state architecture recommendations and modernization sequencing plans.

 

3 months

Modernize the first thin slice

 

Deliver the first production modernization slice from the legacy estate using modern AWS-native architecture and AI-enabled engineering workflows.

 

 

You leave with platform engineering foundations, delivery patterns, governance controls, operational telemetry and modernization operating practices that accelerate future modernization waves.

 

Hero customer story

Client story
A leading manufacturer retired a high-risk mainframe in 5 months and never paused the business.

A North American manufacturer needed to retire a critical mainframe warranty platform that was costly to run, slow to change, and dependent on a shrinking pool of mainframe engineers. We modernized it onto AWS using AI/works™ and AWS Transform in roughly 5 months, against an original 18-month plan, an 80% acceleration. Every cutover was validated against live production behavior, so the business never paused, and behavioral parity was provable at every step.

Read more
Modernization is no longer just about moving systems. AWS Transform and AI/works™ help enterprises rationalize legacy estates, preserve business intent and continuously evolve toward AI-ready operational platforms.
Brian Blanchard
Global Vice President of Cloud, Thoughtworks

Explore what powers it

 

AWS Transform is AWS's agentic AI service for large-scale migration and modernization. AI/works™, our Agentic Development Platform, runs natively on top of it, applying engineering patterns and enterprise context to turn generic outputs into business-specific software. Around both sits three decades of Thoughtworks engineering, including the Strangler Fig pattern by our Chief Scientist Martin Fowler, the proven way to modernize incrementally and retire legacy systems safely.

AWS services your prototype may use

 

Amazon Bedrock for model orchestration and guardrails. Amazon SageMaker for advanced AI workflows. AWS Lambda, Amazon DynamoDB and Amazon CloudWatch for scalable, observable architectures. AWS Mainframe Modernization Service and AWS Migration Hub where the engagement involves mainframe or large-estate migration.

Why Thoughtworks

 

 

  • AWS Premier Tier Services Partner and AWS Data and Analytics Global Partner of the Year, 2025

  • AWS Agentic AI Specialization launch partner

  • AWS Mainframe Modernization and Security Competencies

  • AWS Industry Specializations: Financial Services, Retail, Automotive and Manufacturing, Life Sciences

  • AWS Marketplace ready

  • Active Strategic Collaboration Agreement in place with AWS, co-investing in joint growth for our clients

  • 600+ AWS-certified Thoughtworkers and three decades of large-scale engineering practice

  • Technical foundation built on the Strangler Fig pattern by our Chief Scientist Martin Fowler

Already work with AWS?

Access this workshop through AWS Marketplace to streamline procurement and make use of available AWS funding programs

3-day AI/works™ Discovery Workshop

Meet our leaders

Frequently asked questions

  • It is the first phase of a fixed-price, outcome-based modernization engagement. Three days to align stakeholders, map the legacy estate, identify modernization seams and shape your modernization roadmap. The workshop pairs with a 3-week assessment and proof of value to take you from initial alignment to a working modernization prototype in four weeks. AWS-funded for qualifying engagements.

  • Alignment on modernization goals and constraints. Initial rationalization hypotheses. Identified modernization seams and thin-slice candidates. Legacy context library inputs. Candidate disposition strategies. A modernization roadmap framework. Agreement on the 3-week assessment and proof-of-value scope. Executive alignment on priorities and outcomes.

  • The 3-day workshop is fully AWS-funded for qualifying engagements. The 3-week assessment and proof of value is fixed-price and typically AWS-funded through programs like the AWS Agentic Catalyst Program and MAP. We confirm the exact funding path in the first conversation.

  • Modernizing for AI requires more than moving workloads. The operational intelligence locked inside legacy systems has to be recovered and made accessible to AI. AI/works™ extracts that intelligence into a reusable context library; AWS Transform accelerates the technical migration and modernization; together they produce a modernized system that AI can interact with, evolve, and act on. The Strangler Fig pattern Martin Fowler authored is how we modernize incrementally without pausing the business.

  • CIOs, CTOs, Chief AI Officers, Chief Architects and Heads of Engineering with legacy estates standing between them and AI-ready operations. Most relevant for organizations with mainframe, .NET, Java monolith, Oracle or other enterprise legacy systems carrying significant business intelligence.

  • The 3-month thin-slice delivery follows. We modernize the first bounded capability from your estate, in production, on AWS, establishing the platform foundations, delivery patterns and governance that accelerate every transformation wave after. Most engagements continue into ongoing modernization across the estate.