Proof

Measured, not marketed.

Every figure on this page comes from a real project run through our own pipeline. We publish what we measured; we don't round up, and we don't publish what we didn't measure.

Four projects, three different stacks — .NET on MS SQL, .NET on a Progress database, and Next.js on Postgres — delivered through one stack-agnostic pipeline, one of them running in production. These are recent deliveries, not the limit: the pipeline builds on the stack your standards require.

A retailer-licensing system — specified, proposed, and built

Our flagship: a web-based retailer licensing application system for a state program. First the specification — the kind that anchors a procurement — produced in days, not months:

7Business processes mapped
30Use cases
395Requirements
146Screen specifications
30Clickable prototypes
431Test cases specified

Then the delivery: a working system — .NET 8 on MS SQL — built from that specification in three weeks, alongside the full bid pack the same pipeline produced: the proposal, the compliance response, the price sheet, and a clickable demo an evaluation panel can walk through.

A contract-lifecycle-management system — a different stack entirely

The same pipeline delivered a contract lifecycle management system as .NET on a Progress (OpenEdge) database — the kind of stack constraint real agencies actually have. No re-tooling, no exceptions: the specification, prototypes, and build kit adapt to the accepted technology decision, not the other way around.

The pilot that proved the machinery

A deliberately compact contractor-licensing build — three core use cases, Next.js and Postgres — that we used to prove the delivery machinery end to end: document-first intake, guided search, a security assessment, and the full change cycle. It stands today at 487 passing automated tests and a 43/43 end-to-end walkthrough, verified August 19, 2026.

After delivery, the requirements changed — as they always do. A change kit containing only the delta added an entire search module; a reconcile step then verified the delivered code against the updated specification before handover. Small system, full machinery — that was the point.

An event-management system — in production

The first delivered system running live at a client: an event-management platform for a community non-profit — registration, payment declarations with review, slot booking, a cultural programme, expenses, inventory, announcements and reports under a three-role model. Built on Next.js and Postgres and delivered in under three weeks, specification to live; it is taking real registrations and bookings today.

56/57use cases delivered — one held for Phase 2
604requirements delivered
229prototype screens approved before build
777test cases specified
891automated tests passing (real Postgres, no mocks)
10business processes mapped

Every use case in the delivered scope was walked through as a clickable prototype before it was built. The specification covers more than was built — on purpose: the client went live on a first release that works, holding a fully specified Phase 2 they can commission when they want it.

The Challenge stage — calibrated against reality

Before any build, an independent AI review pass — the Readiness Review — interrogates every finished use case and produces numbered clarifications: the question to ask, plus the default a builder would otherwise assume. We measured it the only way that matters: against the gaps that actually surfaced after a build.

It found 7.5 out of 10 of them in advance. It fabricated zero findings.
We publish the miss rate alongside the hit rate, because a review you can trust is one that tells you what it is.

WHAT WE DON'T CLAIM

Measured projects, not a long track record. The licensing and contract-lifecycle systems are production-ready, built and tested with fictional data, and not yet deployed; the event-management system is in production with real data. Not included in any of these builds, and scoped separately: a software bill of materials and a formal accessibility audit. Deploying into your production environment — real data, live integrations, your security review — is a human-led phase we run with you.

We publish what we measured. We don't round up.
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