Thought Machine and AWS launch AI tool for banking core migration

Vault Forge and AWS Transform combine to compress multi-year banking mainframe migrations into days using frontier AI models.

By Disrupts Editorial Team Tue, 20 October 2026 AI level 2 of 5

AI level 2 of 5: drafted by our AI editorial assistant from the company's announcement; fact-checked, edited and signed off by Mark Walker, Editorial Director. What the levels mean

A modern control room features multiple rows of white desks with ergonomic chairs and curved multi-monitor setups displaying abstract data, brightly lit by large windows on the left.

Thought Machine, the London-headquartered cloud-native core banking company, has partnered with Amazon Web Services to release an AI-powered migration pipeline designed to eliminate one of financial services' most intractable operational problems: the decades-old mainframe. The joint solution, Vault Forge powered by Amazon Bedrock, uses large language model agents to extract business logic from legacy code, including COBOL, and rebuild it as tested, cloud-native Python financial products, compressing what have traditionally been multi-year migration programmes into days.

The announcement lands at a moment when the cost of legacy infrastructure has become a genuine competitive liability for large banks. Regulatory demands around real-time payments, open banking, and instant credit decisioning are accelerating, while the engineering talent capable of maintaining COBOL-era systems continues to age out of the workforce. The pressure to modernise is no longer a technology question; it is a balance-sheet and talent question.

From code translation to business rule extraction

The architecture of the joint pipeline marks a meaningful departure from previous migration approaches. Earlier attempts at mainframe modernisation typically translated legacy code line by line, preserving the structural complexity of the original system and carrying its embedded risks into the new environment. Vault Forge instead targets the business intent beneath the code: interest calculations, fee schedules, repayment workflows, and account lifecycles are extracted as structured specifications before being synthesised into Thought Machine's Vault platform format. Human-in-the-loop review gates at each of four integrated stages give bank risk and engineering teams explicit sign-off authority before any generated product moves to a sandbox environment.

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."

Thought Machine reports it is the first core banking technology company to partner with AWS Transform's modernisation agents. The company has raised more than £500m in funding to date and counts over 65 banks and financial institutions among its clients, several of which are also strategic investors.

The broader convergence at stake

For cross-sector strategists, the story extends well beyond a single product launch. Banking core modernisation has historically been the single largest drag on financial institutions' ability to deploy AI at scale: you cannot build a real-time, AI-driven credit model on top of a batch-processing mainframe. The Thought Machine and AWS approach, if it delivers on the migration-time compression it describes, effectively unlocks a new layer of AI deployability across retail banking, transaction banking, and payments infrastructure simultaneously.

The capital implications ripple outward. Cloud hyperscalers have long targeted financial services as a high-margin vertical, but mainframe inertia has capped the addressable wallet. A credible AI-assisted migration path removes that cap, intensifying competition between AWS, Microsoft Azure, and Google Cloud for core-banking mandates. For fintech infrastructure investors, the question is whether the migration layer itself becomes a durable business or a one-cycle catalyst: once the world's major banks have completed their cloud transitions, the demand profile for migration tooling shifts sharply. The more durable prize is the recurring cloud and platform revenue that follows migration, and Thought Machine's equity position with several client banks suggests it is already positioned to capture a share of that upside.

Regulators in the UK and EU are also watching closely. The Bank of England's operational resilience framework and the EU's Digital Operational Resilience Act both impose concentration-risk scrutiny on cloud adoption by systemically important institutions. Any migration programme of the scale this tool targets will require close coordination with prudential supervisors, adding a regulatory timeline dimension that neither the press release nor the product pipeline fully accounts for.