AI-Powered Software Delivery. Specs ship with acceptance tests.
Every spec ships with acceptance tests. AI builds, humans gate every release. Software delivery as a governed pipeline — the way we build everything, offered as a way to build for you.
DELIVERY · AI BUILDS, HUMANS GATEWhat this engagement is
Our delivery platform treats software like the pipeline treats decisions: specs are artifacts with versions and gates; code is generated and reviewed against them; quality runs as executable acceptance criteria; releases require signed go/no-go. The result is speed with evidence — 2-week prompt-to-MVP at the fast end, regulated-grade traceability at the careful end.
AI does the volume: drafting specs from PRDs, generating code against specs, writing and running tests, assembling release notes. Humans do the judgment: every gate — spec approval, code review, quality certification, release — is signed by a named person with the diff in front of them.
Every deliverable answers "who made this, from what, reviewed by whom" — a full audit trail on request. That's what modernisation with proof means when applied to net-new builds.
The numbers behind it
What ships
Spec-driven development
PRD → gated specs → derived stories; nothing builds without an approved spec.
Agentic build
Code generated against specs on our production platform, humans reviewing every PR.
Acceptance-test contracts
Every spec ships with executable acceptance tests — done means proven.
Signed releases
Go/no-go gates with runbooks, evidence packs and named approvers.
2-Week Prompt-to-MVP
The fast lane: from a one-page intent to a working, gated MVP in two weeks.
Full traceability
Spec → code → test → release, linked end-to-end in the graph.
How the engagement runs
Five phases from acceptance-test-first specs to releases that compound.
Proof from production
Specs on Monday, gated releases by Friday
“Acceptance-test-first specs let AI build while humans gate — a weekly release cadence held for months, with regressions caught by the tests before users ever saw them.”
Questions teams ask
Is AI-written production code safe?
The gate is the answer, not trust in the model. Acceptance tests define done before code exists; humans review the diffs and the decisions; nothing merges ungated. Safety is the process.
Where does the speed actually come from?
AI does the volume — scaffolding, tests, migrations, boilerplate — while people spend their time on judgment. We're measured on outcomes shipped, not hours logged.
Who owns the code?
You do, from the first commit. Repositories live in your organisation; specs, tests and decision records are part of the deliverable.
What stacks do you cover?
Web, mobile, data and agent stacks, with code intelligence spanning 13 languages. The spec-and-gate model is the constant; the stack is whatever your estate needs.
Pick your function. Own the intelligence behind it.
Discover one opportunity, engineer one capability, deliver one measurable outcome — then scale.