Thought Machine launches AI banking migration with AWS

By Divya Shah

Thought Machine, a cloud-native core banking and payments technology provider, launched an AI-powered migration solution in collaboration with Amazon Web Services (AWS) to help banks accelerate core banking modernisation programmes. 

The solution combined AWS Transform’s mainframe reverse-engineering capabilities with Thought Machine’s Vault Forge AI tooling suite, enabling financial institutions to modernise legacy systems more quickly, safely, and at a lower cost.  

The offering allowed banks to transform millions of lines of legacy mainframe code, including COBOL, into tested cloud-native financial products within a live sandbox environment, reducing processes that traditionally took years to just days. 

The joint solution extracted business logic from legacy systems within a bank’s secure cloud environment. Thought Machine said this approach helped institutions overcome the challenges associated with traditional core banking platforms, where product logic is embedded directly into underlying databases, making migration projects complex and high-risk. 

The company’s Vault platform defined financial products entirely in Python code, separating product logic from the core infrastructure. This architecture enabled AI agents to translate legacy banking rules, including interest calculations, fee structures, repayment processes, and account lifecycle management, into modern cloud-native products. 

Paul Taylor, CEO of Thought Machine, said, “By combining AWS Transform directly with Vault Forge, we are fundamentally rewriting the economics of core modernisation. For the first time, banks can deploy AI to rapidly convert complex legacy mainframe specifications into simulation-tested, cloud-native financial products. This gives large financial institutions the execution speed, audit rigor, and confidence required to eliminate technical debt and complete their cloud transition.”

The solution simplified modernisation initiatives for major national and global financial institutions by accelerating tasks such as code analysis, dependency mapping, and migration validation. Banks were provided with early proof of migration outcomes through an AI-guided process operating entirely within their secure AWS environments. 

The migration pipeline was delivered through four stages: extraction, consolidation, synthesis, and validation. AWS Transform extracted and reverse-engineered legacy applications into structured business requirements, while Vault Forge utilised AI agents through Amazon Bedrock to generate SDK-compliant Python financial products, test suites, and platform configurations.  

Human-in-the-loop review processes ensured that banks maintained full approval authority before deployment into a Vault sandbox environment. 

To support adoption of the solution, Thought Machine also launched its Core Modernisation Accelerator programme. Through the initiative, technical architects, product specialists, and forward-deployed engineers worked alongside bank teams to support governance, architecture design, and implementation activities. 

Charith Mendis, Head of Worldwide Banking, Financial Services Industries, Amazon Web Services, said, “With Thought Machine’s Vault Forge and AWS Transform’s AI capabilities, we enable banks to safely extract business logic from legacy systems, providing a new continuous, automated path from mainframe code to cloud-native core banking – solving one of the hardest banking modernisation challenges for banks, and we believe it will fundamentally change how the industry approaches core transformation.”