How we work
The hard part of modernization isn't the code.
It's knowing the new system does what the old one did.
Equivalence testing
Legacy systems carry decades of business rules, many of them undocumented. Some are bugs your business now depends on. We don't guess what the system does; we record it.
We run your current system on real and edge-case inputs and keep its outputs as the reference. The new system must produce the same outputs for the same inputs, record by record. Any difference is either fixed or explained and signed off by you, never ignored.
Where AI helps, and where it doesn't
We use AWS Transform and Claude to analyze code, convert it, and write infrastructure and tests. That makes the mechanical work faster and cheaper.
A principal architect reviews every design and every change, and owns four decisions that are never automated:
- The target architecture
- How the data is mapped and migrated
- The security review
- The go-live decision
Your code and data
- Your code stays in your source control or your AWS account wherever possible.
- AI services run through Amazon Bedrock inside AWS, so your code isn't sent to outside services and isn't used to train models. The exact setup is agreed for each engagement.
- Production data is never copied into our repositories.
- Every deployment goes through an automated pipeline with tests and a human approval.
More detail: AI and data handling.
What you get at the end
Working software on AWS, infrastructure defined as code, an automated pipeline, the equivalence test suite, and runbooks. Everything is yours, with no lock-in.