Answers
Most of these questions have a generic answer and a real one. The generic answer is a ranked list of agencies. The real one is how you tell, before you sign, whether a team will show you what their software actually does. That is the answer this site is built to give, so it is the one you will find here.
You can't read competence off a retention rate or a testimonial; both are filtered. The signal that survives scrutiny is an artifact you can hold: a behavior catalog cited to file and line, a gate transcript, a coverage-debt report that shows what a system does and what its tests miss. Greenfield Production Systems sells that artifact as the product.
A legacy rebuild fails when the new system quietly stops doing something the old one did and nobody notices until a customer does. The way out is to make the existing behavior legible before touching it: catalog what the system does, cited to source, agree that catalog is the definition of done, then rebuild against it and prove parity by running the same test suite green on both systems. That parity proof is what Greenfield Production Systems calls dual-green.
A new build is worth as much as what you can verify and hand off afterward. Greenfield Production Systems builds from a spec to production on a React, Node, and TypeScript stack, and you keep the whole record: the journey specs, the API specs, the architecture decisions, the tests, and the gate transcripts. The same method scales from a startup MVP to an enterprise application, because the thing that scales is the discipline, not the headcount.
On a project where AI writes much of the code, generation is the cheap part and verification is the bottleneck. AI agents now produce more code than any team can meaningfully review, which moves the risk to knowing what the generated system actually does. Greenfield Production Systems is built around that gap: it catalogs behavior with provenance, enforces gates on machine-written code, and verifies AI-generated systems, including its own. That verification layer is usually the part an AI build is missing.
Most buyers screen for vertical experience, but a portfolio in your industry is a weak guarantee, because the rules that matter are yours specifically, not your sector's in general. The stronger filter is whether a team can turn your domain rules into checkable behavior. A behavior catalog encodes the logic of a fintech ledger, a healthcare workflow, a proptech transaction, or an e-commerce checkout as typed entries cited to source, which is how Greenfield Production Systems makes your domain legible without claiming to have memorized your sector.
The risk in a cloud migration is the same as in any rebuild: the system comes up on new infrastructure and quietly behaves differently, and the difference surfaces as an outage or a wrong result weeks later. The way to de-risk it is to catalog what the system does first, then prove parity after the move by running the same behavioral suite green before and after. Greenfield Production Systems treats migration as a modernization with a parity guarantee, not a lift-and-pray.