Delivery speed is a feature.

When releases take six weeks and every deploy is an event, the problem is rarely one tool. It is the accumulated weight of decisions nobody owns. We take one delivery bottleneck, pipeline, platform or cloud infrastructure, own it end to end, and hand back a pipeline your team actually uses.

How we work

1. The bottleneck. DevOps and platform engineering engagements with us are narrow on purpose: one pipeline, one bottleneck, one number to move, cycle time, deploy frequency, mean time to recover. cycle time, deploy frequency, MTTR
2. The stack. Kubernetes and Docker for runtimes, Terraform for infrastructure as code, GitHub Actions for CI/CD, Prometheus and Grafana for observability, on AWS and Google Cloud. Redis and friends where the architecture calls for them. Kubernetes, Docker, Terraform, GitHub Actions, Prometheus, Grafana, AWS, Google Cloud, Redis
3. The build. The deliverable is never a diagram. It is a working pipeline with the old path retired and the team onboarded, releases turned from events into routine. working pipeline, old path retired, team onboarded
4. The hand-over. A before/after measurement of the number we agreed to move, from your own repos. If your platform team inherits it without needing us again, the engagement worked. before/after numbers, no dependency

What we take on

• CI/CD pipelines. The release path automated end to end, build, test, deploy, rollback, until shipping is routine.
• Kubernetes platforms. A platform your team can actually run: clusters, ingress, secrets, autoscaling, golden paths.
• Cloud migration. One workload moved to AWS or Google Cloud, with before-and-after numbers proving nothing broke.
• Infrastructure as code. Terraform that makes the next environment a pull request, not a project.
• Observability & SRE. Prometheus, Grafana and alerting that page a human only when a human is needed.
• Cloud cost optimisation. The bill decomposed, the waste removed, and guardrails installed so it stays down.

Technologies

• Temporal: The candidate pipeline that could not get stuck
• Redis: The candidate pipeline that could not get stuck, The skills engine that became EY Spotmentor, A GenAI platform for an airport, answered with working bots
• Celery: The candidate pipeline that could not get stuck, The skills engine that became EY Spotmentor
• Kubernetes: The skills engine that became EY Spotmentor, A research assistant that reads the literature overnight, Fifteen months to retire the legacy pipeline, A private cloud carved out of the server room, A GenAI platform for an airport, answered with working bots
• Docker: The candidate pipeline that could not get stuck, Identity-anchored AI link discovery with Exa, The skills engine that became EY Spotmentor, A WordPress site rebuilt to deploy itself on Cloud Run, One AI desk over a ministry's scattered knowledge, Fifteen months to retire the legacy pipeline, A private cloud carved out of the server room, From hand-built servers to containers in production
• Terraform: A GenAI platform for an airport, answered with working bots
• GitHub Actions: The candidate pipeline that could not get stuck, From hand-built servers to containers in production
• Grafana: The skills engine that became EY Spotmentor, A private cloud carved out of the server room, A GenAI platform for an airport, answered with working bots
• Prometheus: The skills engine that became EY Spotmentor, A private cloud carved out of the server room, A GenAI platform for an airport, answered with working bots
• AWS: The skills engine that became EY Spotmentor, A WordPress site rebuilt to deploy itself on Cloud Run, A research assistant that reads the literature overnight, Warranty documents that read themselves, One AI desk over a ministry's scattered knowledge, From hand-built servers to containers in production, A GenAI platform for an airport, answered with working bots
• Google Cloud: The candidate pipeline that could not get stuck, Identity-anchored AI link discovery with Exa, A WordPress site rebuilt to deploy itself on Cloud Run
• Cloud Run: The candidate pipeline that could not get stuck, Identity-anchored AI link discovery with Exa, A WordPress site rebuilt to deploy itself on Cloud Run
• Sentry: The candidate pipeline that could not get stuck

For corporates

The release process everyone complains about and nobody can schedule time to fix. We fix it from outside.

For startups

Infrastructure that will not embarrass you at scale, built while you focus on the product.

The evidence

Cycle-time and deploy-frequency numbers, before and after, from your own repos.

The way we engage

• Senior engineers, no intermediaries. The people on the call are the people writing the code. Questions get same-day answers, not a follow-up meeting.
• A working build every week. Progress arrives as running software, not status decks. Every drop is something you can put in front of a user.
• Fixed price, never a meter. The price is agreed before we start. If we scoped it wrong, that is our cost of learning, not your overrun.
• You own everything. Code, infrastructure and documentation transfer at hand-over. No licences back to us, no dependency by design.
• Candour in week zero. If the problem needs rethinking, we say so before the build starts, not after the budget is spent.
• Across your time zones. US, European, Gulf and ANZ coverage, with overlap hours agreed at kick-off.