GCP engineering — the cloud where data and AI workloads tend to be the deciding factor. GKE for Kubernetes, Cloud Run for serverless containers, BigQuery for analytics, and Vertex AI when the model surface is meaningful.
We pick GCP when BigQuery or Vertex AI are commercially load-bearing, and we ship it with the same landing-zone and IAM discipline we apply to AWS or Azure. Hierarchical resources and Organisation Policies are the floor.
A GCP estate where data, AI, and product teams can move without trampling each other's IAM or quota.
Concrete deliverables — not adjectives. Each engagement scopes which of these are in play and what success looks like for them.
Drawn from sales calls, not SEO filler. Want a question added? Drop it in the form on this page — we update from real enquiries.
Cloud Run for stateless services and most product backends. GKE when you have Kubernetes-shaped requirements (StatefulSets, custom controllers, multi-tenant platform).
When BigQuery is the data-warehouse decision, when Vertex AI's tooling is meaningfully ahead for the workload, or when the team has GCP muscle memory.
Yes — Firebase services are GCP. We use Firebase Auth, Firestore, and Cloud Functions where they fit, and graduate to GCP-native (Postgres, GKE) when the workload outgrows Firebase shape.
Not categorically. Single-cloud is simpler. Multi-cloud is justified when there are real reasons (procurement, data residency, vendor concentration risk). We'll be honest about the operational cost.
AWS engineering with the discipline most agencies skip — multi-account landing zones, least-privilege IAM, infrastructure-as-code from the first commit, and FinOps that catches the spend before the CFO does.
Azure engineering for organisations that are Microsoft-shaped — by procurement, by identity (Entra ID / Active Directory), or by line-of-business stack.
Vercel engineering for teams who want to ship fast and stay shipping fast.
Firebase as a real backend — Firestore modeled with the right indexes and security rules, Cloud Functions v2 with structured logging, and Auth integrated with the rest of the identity story instead of bolted to the side.
