Get in Touch
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SDLC Transformation

Your Team Has AI Tools,
but What It's Missing
Is a Method

We install an AI delivery pipeline into your own repositories, prove it on your own next features, and leave your engineers running it.

Book a Discovery Meeting Talk to an Architect (30 min)

The Engine Pointed at
Your Delivery Process

Nothing gets rebuilt here. The code stays exactly where it is. What changes is how software gets produced: specifications drafted by agents and owned by your people, builds run in parallel, a machine check before every merge, and your engineer holding the sign-off.

We build a knowledge core over your live estate, the same evidence-first capture we would do before a modernisation but for a different purpose: to power your ongoing delivery rather than to produce a plan. Then we install the pipeline into your own repositories and your own CI. Your next real features run through it. Your engineers hold the decision seats from the first day, not after a handover phase.

The old process is retired gradually, workstream by workstream, as the new one earns each one. There is no day-one switchover, because a process big-bang fails the same way a data big-bang does.

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Who It's For

Engineering organisations of maybe thirty to several hundred people where the product is live and earning, lead time is getting worse rather than better, and AI tools are already in the building with uneven results. Usually the trigger is a CTO who has been asked what the AI investment produced and does not have a good answer.

The Problem & Our Solution

Why Delivery Gets Slower Every Year

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Every feature costs more than the last one.
The codebase aged, the shortcuts accumulated, and lead time grows quietly until someone notices it in a board pack.

Every feature costs more than the last one. The codebase aged, the shortcuts accumulated, and lead time grows quietly until someone notices it in a board pack.
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Our Solution :
A knowledge core over your estate that compounds. Every feature shipped through it makes the next one cheaper, because understanding stops being re-derived from scratch.

Our Solution : A knowledge core over your estate that compounds. Every feature shipped through it makes the next one cheaper, because understanding stops being re-derived from scratch.
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Critical knowledge lives in three people's heads.
Two are on holiday and one is interviewing elsewhere. Regression fear slows every release.

Critical knowledge lives in three people's heads. Two are on holiday and one is interviewing elsewhere. Regression fear slows every release.
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Our Solution :
The estate's behaviour becomes a cited, structured record in your repositories. Fear of breaking things gets replaced by a test that tells you whether you did.

Our Solution : The estate's behaviour becomes a cited, structured record in your repositories. Fear of breaking things gets replaced by a test that tells you whether you did.
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AI tools are in the team and running loose.
No guardrails, output nobody can explain, results that depend on who prompted it. Adoption without a method produces risk rather than speed, and the industry data on this is not flattering.

AI tools are in the team and running loose. No guardrails, output nobody can explain, results that depend on who prompted it. Adoption without a method produces risk rather than speed, and the industry data on this is not flattering.
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Our Solution :
The guardrails as running code in your CI: rules, hooks, templates, the review gauntlet, two gates. Not a policy document. Something that blocks a merge.

Our Solution : The guardrails as running code in your CI: rules, hooks, templates, the review gauntlet, two gates. Not a policy document. Something that blocks a merge.
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You cannot tell whether the AI investment is working.
Anecdotes from enthusiastic engineers, no measurement, no baseline.

You cannot tell whether the AI investment is working. Anecdotes from enthusiastic engineers, no measurement, no baseline.
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Our Solution :
Lead time measured on your own features, gate by gate. If it is not improving we would both rather know.

Our Solution : Lead time measured on your own features, gate by gate. If it is not improving we would both rather know.
How It Works

Install It, Prove It On Your Work, Hand It Over

01

Build The Knowledge Core Over Your Live Estate

Agents read the code, the data and the dependencies. Your people validate. The same capture as a modernisation assessment, and the asset the whole transformation rests on.

02

Install The Pipeline Into Your Repositories

Rules, hooks, templates, agent roles, the six-phase loop and both gates, wired into your CI and review flow. Your engineers hold the human gate from the start. Agents never merge, in your organisation exactly as in ours.

03

Run Your Real Backlog Through It

Your next actual features are the proof, not a workshop exercise. An acceptance harness protects the behaviour you already have on every merge.

04

Retire The Old Process Gradually

Workstream by workstream, as the pipeline earns each one. Nothing is retired by announcement.

05

We Leave

The deliverable is your team operating the method. This is a transfer, not a staffing arrangement, and we would rather say that clearly than sell you an ongoing dependency.

What You Get

A Production Line That Is Yours

Shorter Lead Time Without Quality Erosion

Measured on your own features, gate by gate, against your own baseline.

Shorter Lead Time Without Quality Erosion

A Knowledge Core That Outlives Any Individual

It compounds with every feature rather than decaying like documentation does.

A Knowledge Core That Outlives Any Individual

Guardrails That Are Running Code

A machine check wired to branch protection blocks a bad merge. A policy document does not.

Guardrails That Are Running Code

Your Engineers In The Decision Seats

Specification ownership, architecture calls, merge authority, final acceptance. Reserved for humans by design.

Your Engineers In The Decision Seats

A Method That Is Yours When We Go

The pipeline runs on standard CI in your own repositories. There is no platform to keep paying for.

A Method That Is Yours When We Go

Evidence

What Is Proven And What Is Not

The pipeline, the guardrails and the gates have run end to end on a real regulated modernisation programme. That part is not theoretical, and we will walk you through it under NDA: the agent runs, the pull requests, the gate results, the costs.

What we have not yet done is install it inside a customer's own organisation and hand it over with them operating it. This line is offered on proven machinery and an unproven transfer, and we will say the same thing on the call. The first customers on it get priced accordingly.

FAQ

We can adopt AI tools ourselves. Why an engagement?

You can, and many of our conversations start with a team that already has. Tools are the smallest part. What you are buying is the installed discipline and the transfer of it, which is the part that makes the speed safe to trust.

Will this disrupt delivery while it lands?

No big-bang. The pipeline earns workstreams progressively, proving itself on your next real features while the old process keeps running everything else.

Our engineers will think they are being replaced.

They are not, and the method's structure is the argument rather than the reassurance. Four kinds of decision have no agent route at all: specification ownership, architecture, merge authority and final acceptance. In practice engineers move from writing the volume to deciding what is correct.

How do you measure whether it worked?

Lead time on your own features, gate outcomes, and the rate at which existing behaviour gets broken. We take a baseline before we start, because otherwise the whole exercise is anecdote.

Which tools and models does it use?

Set per engagement, on your infrastructure and your data boundaries, agreed before anything is ingested. The method does not depend on one vendor's model.

How long does it take?

The knowledge core and the first installed workstream are a matter of weeks, not quarters. Full retirement of the old process depends on how many workstreams you have and how fast you want to move.

Fix The Production Line, Not Just The Tools

We start by measuring how your delivery actually works today and installing the pipeline on one workstream. You see it running on your own features before you commit to the rest.

Book a Discovery Meeting Or Talk To an Architect For 30 Minutes First?

Let's Work Together

We are happy to help you transform your DevOps infrastructure and accelerate your delivery pipeline.

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