Services

$ ls services/

From legacy estate to AI-augmented delivery platform — pick the entry point, we'll meet you there.

platform --build

Platform Engineering & Internal Developer Platforms

Build the reusable path to production — scaffolding, shared pipeline libraries and golden paths — so the tenth service ships faster than the first.

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pipeline --standardise

CI/CD Modernisation

Replace copy-pasted pipeline YAML with a versioned, composable library — and a release process where every artefact traces back to an exact commit.

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k8s --deliver

Kubernetes & Container Delivery

Production Kubernetes delivery — Helm charts, TLS ingress, dependency-aware health checks, environment-gated promotion and a teardown path that works.

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cloud --transform

Cloud Migration — Azure & AWS

Move ageing infrastructure to Azure or AWS in stages the business can absorb — assessed, sequenced, and described in code from the first environment.

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secops --shift-left

Security Engineering & DevSecOps

Make security a property of the pipeline: secret scanning as a merge gate, hardened images, signed artefacts, and policy that fails builds rather than filing tickets.

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governance --declare

Governance & Compliance as Code

Projects, repositories, branch policies, environments and approvals reconciled from version-controlled YAML — reviewable, auditable and reproducible.

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build --modern

Application Development & Modernisation

Build and modernise applications with the delivery path attached — Node and TypeScript services, APIs, internal CLIs and reusable packages.

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ai --to-production

AI Engineering & LLM Integration

Put language models into production safely — server-side credential custody, retrieval over your own content, tool-layer authorisation and cost ceilings.

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slo --define

Reliability & Observability

Move from deploy-time confidence to runtime confidence — health checks that tell the truth, then metrics, alerting and service objectives that reflect user experience.

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cost --right-size

FinOps & Cost Optimisation

Most cloud and AI overspend is structural, not wasteful usage — over-reserved compute, unbounded context and no ceilings. All three are fixable.

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Not sure where to start?

A one-hour architecture review is usually enough to find the first win.

Talk to an architect