Fast software you can actually trust

AI-generated code ships with roughly 1.7× the issues of human-written code. A third or more of AI-written snippets carry a known class of security flaw. Left unmanaged, AI-built systems push maintenance costs toward 4× by year two. The gap between shipping fast and shipping something you can trust is widening every month, and that gap is exactly where we work.

WeServ's quality engineering practice is built on more than a decade of test leadership and release engineering at Lloyds, BBVA, Crédit Agricole and Ion Group / MarketFactory: trading and banking systems where a bad release moves money and breaks regulation. That discipline, applied to your codebase, is what turns "it seemed to work when we tried it" into "it is verified to work, and we will know immediately if that changes."

The system. A multi-product financial platform for small businesses: payments, lending, rotating savings, a voice-AI assistant. Forty data models, around a hundred and twenty API endpoints, several user roles: the kind of surface area where money moves through many paths and a quiet break in one of them is a real loss.

The risk. It was built fast. Fast building is how the product existed at all, but speed is exactly where defects hide: edge cases in lending logic, a savings cycle that miscalculates, an endpoint that accepts what it should reject.

What we built. A suite of more than 2,200 automated tests covering the platform's models, API surface and business logic. Money paths, lending rules and savings cycles tested as logic, not clicked through by hand. The system's own code now says the moment something breaks.

Why it matters. Anyone can ship software quickly now. The harder, rarer thing is shipping it quickly and being able to trust it in production. A test suite of this depth is what separates a demo from a deployable financial product.