DevOps, platform engineering and AI coding harnesses
A tested path from commit to production, for your engineers and their AI coding agents
Where delivery slows down
Many delivery problems are not in the code. They are in manual deployments, environments nobody can rebuild and release steps that only one person knows. Every team builds its own pipeline, and every new service starts with its own set-up work.
AI coding agents add a new risk: they can produce changes faster than people can review them. Without automated checks, plausible but unverified code reaches production.
What changes for you
Environments you can rebuild
Every environment is defined in code and can be recreated on demand, so a failed server or a new region is routine work.
Routine releases
Build, test, scanning and deployment run the same way for every service, with approvals where your controls require them.
AI-written code you can trust
Changes from people and from coding agents pass the same automated gates before they merge.
What we deliver
AI coding agent harnesses
Coding agents set up inside your repositories with the context, tools and permissions their tasks need and nothing more, so their work follows your standards. A harness is the controlled environment an agent works in.
Automated code-verification gates
Tests, type checks, security scans and policy checks that every change must pass before it merges, whoever or whatever wrote it.
Infrastructure as code
Every environment defined in Terraform, OpenTofu or Pulumi and reviewed like application code. Infrastructure as code (IaC) means servers, networks and permissions are written as files and applied by tools, not configured by hand.
GitOps provisioning
Changes to environments are made through reviewed commits and applied automatically, so what runs always matches what is in the repository.
CI/CD and release automation
Continuous integration and delivery pipelines that build, test, scan and deploy every change, with releases that can be repeated and rolled back.
Containers and Kubernetes
Kubernetes clusters, with a service mesh where traffic between services needs it, and deployment templates your teams reuse.
Internal developer platform
A self-service platform on Kubernetes where teams create services, environments and pipelines from approved templates instead of raising tickets.
Secret vaults
Credentials kept in a managed vault and rotated automatically, never written into code or pipeline settings.
How the work runs
Assess
We review how code reaches production today, where it waits, what breaks and which controls you must meet.
Design the platform
We agree the templates, gates, tools and responsibilities with your engineers, starting from what already works.
Build the foundation
We set up infrastructure as code, the vault, the pipelines and the first templates, all reviewed like application code.
Move services across
We move services onto the platform one at a time, each with a rollback path, and fix what the first ones reveal.
Hand over
We pair with your engineers on releases and incidents, write runbooks for the common tasks and step back as they take over.
How we prove it in our own work
We deliver our own projects this way. Every engagement starts with environments provisioned as code and secrets in a vault, and every sprint runs through automated code-verification gates.
- DevOps and observability
- Terraform
- Pulumi
- OpenTofu
- Kubernetes
- Docker
- Helm
- GitLab CI/CD
- GitHub Actions
- Argo CD
- Security and cryptography
- HashiCorp Vault
How to start
What happens next
Pre-consulting session
A free 30-minute online pre-consulting session: we go through your goals, systems and constraints.
Readiness review
In a free 48-hour readiness review, a Principal Architect checks your project against the 6-point Definition of Ready and recommends the track that fits.
Choosing the track
Scope-ready projects receive a binding proposal within 3–5 business days. Concept-stage projects start in the Blueprint Studio. A live system that is failing, undocumented or needs integration starts with a diagnostic of 1–2 weeks. The Blueprint Studio and the diagnostic each have a fixed fee, quoted in the proposal.
Delivery in five stages
Mobilisation, sprints with live demonstrations, integration and hardening, acceptance and go-live, then managed services. After launch comes a warranty period, then optional support and maintenance.
AI-native product teams
Managed, cross-functional pods of senior engineers, equipped with agentic coding and QA harnesses.
Embedded specialists and strategic augmentation
Nearshore and on-site principal engineers and specialists, and embedded solution, transformation, PQC and integration architects.
The quickest way in is the Cloud portability and AI token FinOps audit package, one of our rapid engagement packages.
Questions and answers
What is platform engineering, and how is it different from DevOps?
DevOps is the practice of developers and operations sharing responsibility for running software. Platform engineering turns that practice into a product: an internal developer platform that gives every team the same tested way to build, deploy and run services. Your teams spend their time on features, not on pipelines.
Is it safe to let AI coding agents change our code?
It is when the agent works inside a harness. The agent gets only the access its task needs, its changes go through review like anyone else's, and the same tests, scans and policy checks must pass before anything merges. Nothing an agent writes reaches production without passing those gates.
Which tools do you use?
Usually the ones you already have. We work with Terraform, OpenTofu and Pulumi for infrastructure, Kubernetes for containers, and the common CI/CD services, including GitLab CI/CD, GitHub Actions and Argo CD. We recommend a change only when a tool blocks what you need.
We already have pipelines. Do we have to start again?
No. We start from what works, standardise it into templates and replace only the parts that are fragile or missing. Services move onto the platform one at a time.
How do you secure the platform?
Identity comes first: single sign-on, least-privilege roles and no shared credentials. Secrets live in a vault, guardrails block insecure configurations before they are deployed, pipelines scan code, dependencies and container images for known vulnerabilities, and audit logs are kept where nobody can alter them.
Will our team be able to run the platform afterwards?
That is the aim. Everything is defined as code and documented, and your engineers review and approve changes with us from the start. If you prefer us to keep running the platform, that can continue under a managed services agreement.
Ready to build? Ask for a proposal.
Send your requirements or RFP. Our architects validate them and return a binding, fixed-scope proposal.
What happens next
Readiness review
In a free 48-hour readiness review, a Principal Architect checks your project against the 6-point Definition of Ready and recommends the track that fits.
Binding proposal
After architecture validation at no cost, you receive a binding, fixed-scope proposal within 3–5 business days: milestones, architecture, team structure and SLAs. We sign a non-disclosure agreement (NDA) with you on request, before you share your requirements.
Mobilisation
Once you sign, our engineering pods begin Sprint 0 within 5–10 business days of contract signature.
Delivery in five stages
Mobilisation, sprints with live demonstrations, integration and hardening, acceptance and go-live, then managed services. After launch comes a warranty period, then optional support and maintenance.