Infrastructure Engineer

Thought Machine, AWS tap AI to help banks move beyond legacy systems. The migration process runs within each bank's secure AWS environment. Get the hottest Fintech Singapore News once a month in your Inbox Thought Machine has partnered with Amazon Web Services (AWS) on an AI-powered solution for banks moving from legacy systems to its Vault core banking platform. The solution combines AWS Transform's mainframe discovery and reverse engineering tools with Vault Forge, Thought Machine's AI tooling suite. It aims to reduce the time and cost of core banking migration, according to Thought Machine. Rather than translating legacy code line by line, the process extracts the business rules behind functions such as interest calculations, fee schedules and loan repayments. The Vault platform keeps financial product logic separate from its core infrastructure. This separation allows AI agents to convert legacy rules into product code while bypassing database complexities. The process runs within the bank's secure AWS environment. AWS Transform analyses legacy applications and extracts their business logic into structured specifications. The pipeline then consolidates redundant legacy product variations before Vault Forge uses AI models through Amazon Bedrock to generate Python-based financial products, test suites and platform configurations. Bank engineering and risk teams retain sign-off authority through human review stages. Once validated, the generated products can be deployed to a Vault sandbox for further testing and evaluation. According to Thought Machine, the approach can compress multi-year processes into days, including work involving millions of lines of mainframe code. Paul Taylor, CEO of Thought Machine, said: "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." Charith Mendis, Head of Worldwide Banking, Financial Services Industries, AWS, 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." Thought Machine is also launching a joint Core Modernisation Accelerator programme with AWS. Technical architects, product specialists and Thought Machine engineers will work alongside bank engineering teams on implementation, governance and architecture. Featured image: Edited by Fintech News Singapore, based on image by mrsiraphol via Magnific

Thought Machine and AWS launch AI tool to accelerate legacy core banking migrations. Thought Machine and Amazon Web Services (AWS) have launched a joint AI-powered migration solution designed to automate the transition from legacy mainframe systems to cloud-native core banking. By converting COBOL code into modern Python-based financial products, the partnership aims to drastically reduce the time, risk, and cost associated with traditional bank modernisation projects. What was announced. The new solution integrates AWS Transform's mainframe reverse engineering tools with Thought Machine's Vault Forge, an AI-driven tooling suite. The primary objective is to allow major national and global financial institutions to reimagine millions of lines of legacy code - specifically COBOL - into tested financial products within a secure cloud sandbox. Unlike traditional migration methods that translate code line-by-line, this pipeline extracts the underlying business intent within the customer's secure environment. The process is divided into four distinct stages: Extraction, Consolidation, Synthesis, and Validation. First, AWS Transform performs discovery on legacy applications to extract logic into Easy Approach to Requirements Syntax (EARS) specifications. These are then consolidated to remove redundant product variations. In the synthesis phase, Vault Forge uses AI agents via Amazon Bedrock to generate SDK-compliant Python code for financial products, including interest calculations, fee schedules, and repayment workflows. Finally, a "Human-in-the-Loop" review gate ensures bank staff can sign off on the logic before deployment to a Vault platform sandbox. To facilitate adoption, Thought Machine is also introducing a Core Modernisation Accelerator programme. This initiative provides banks with access to technical architects, product specialists, and engineers to manage the governance and architecture setup. The solution operates entirely within the bank's existing AWS environment, ensuring data security while accelerating multi-year programmes into significantly shorter timeframes, potentially compressing processes that usually take years into days. "We built Thought Machine on a single, uncompromising mission: to properly and permanently free the world's banks of legacy technology. Our partnership with AWS marks a massive leap forward in fulfilling that promise. 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 companies involved. Thought Machine is a cloud-native core banking and payments technology provider. The company's flagship product, Vault, is designed to replace legacy core systems by defining financial products as code using Python, rather than hardcoding them into database infrastructure. This decoupling of product logic from core infrastructure is a central component of their market position, allowing for greater agility in product development for incumbent banks. FF News has featured Thought Machine in 51 stories to date. Amazon Web Services (AWS), a subsidiary of Amazon, is a dominant provider in the global cloud infrastructure market and has been the subject of 111 reports by FF News. Through its Worldwide Banking and Financial Services Industries division, AWS provides specialized tools like AWS Transform to help highly regulated institutions move away from on-premises hardware. Charith Mendis serves as the Head of Worldwide Banking Industry at AWS, overseeing the strategic direction for financial services clients globally. Together, these companies represent a significant shift toward the "as-a-service" model for the foundational layers of global finance, providing a continuous path from mainframe code to cloud-native core banking. What FF News has reported before. FF News has closely followed the intersection of AI and cloud infrastructure within the financial sector. Ascento Capital recently reported on how Ramp Partners With AWS to Bring AI Finance Operations to AWS Marketplace, highlighting the growing trend of AI-enabled financial services. Additionally, the infrastructure side of the market was highlighted when OpenAssets Launches Institutional Tokenization Infrastructure on AWS Marketplace. Broader industry movements also reflect this shift toward modernization. Innovate Finance Urges UK Action on Open Finance and AI to Secure FinTech Lead, emphasizing the regulatory and competitive pressure on banks to adopt these technologies. Furthermore, the investment landscape remains active, as seen when Molten Ventures Secures £175M First Close for New European Growth Fund, providing capital for the next generation of fintech innovators. What this means. This announcement signals a critical shift in the "buy vs. build" debate for Tier 1 banks. For years, the sheer volume of COBOL code has acted as a moat protecting legacy vendors, as the risk of manual migration was deemed too high for most boards to stomach. By applying generative AI to reverse-engineer business intent rather than just syntax, Thought Machine and AWS are attacking the primary bottleneck of digital transformation. This puts immense pressure on traditional core banking providers who rely on long-term maintenance contracts for legacy systems. The industry must now address whether AI-guided validation is sufficient to satisfy regulators in the event of a systemic migration failure. Featured speakers.