Google Cloud Platform (GCP)
GCP is the cloud Google built for how Google runs software — which makes it exceptional exactly where we live: GKE is the best managed Kubernetes in the business, BigQuery redefined what a data warehouse should cost to operate, and Vertex AI puts serious model infrastructure behind an API. For engineering-led organizations, it's frequently the right answer.
We build GCP platforms with the same spine as everything else we ship: organization hierarchies and landing zones done first, GKE run with real platform discipline — Workload Identity, network policy, autoscaling that respects budgets — Vertex AI and Gemini wired in where your data already lives, and committed-use economics negotiated with evidence. No cloud-migration theater; a platform your team runs with confidence.
GKE platform engineering
Production clusters with Workload Identity, network policy, and node economics tuned to your load.
Landing zones
Organization hierarchy, IAM, and VPC design that scale past the first project without regret.
Vertex AI integration
Model serving, RAG, and agents inside your GCP perimeter and IAM model.
BigQuery architecture
Warehouse design, partitioning, and cost controls — analytics without the surprise invoice.
Cost engineering
Committed-use discounts, right-sizing, and autoscaler tuning grounded in usage data.
Why GCP over AWS or Azure?
If Kubernetes and data are the center of your platform, GCP's GKE and BigQuery are genuinely best-in-class, and the developer experience is cleaner. If your gravity is Microsoft licensing or AWS-native services, the calculus shifts. We work across all three and recommend from your workload, not our preference.
Can you help with multi-cloud?
Yes, with a warning: multi-cloud by design is expensive, and most companies arrive there by acquisition, not intent. Kubernetes and Terraform keep workloads portable where it matters; we'll help you be deliberately multi-cloud instead of accidentally so.
Is Vertex AI a real alternative to calling model APIs directly?
For teams whose data and compliance boundary live in GCP, yes — model access governed by your existing IAM, close to your BigQuery data, with grounding and eval tooling attached. We integrate it where that boundary matters and go direct-to-API where it doesn't.
Put Google Cloud Platform (GCP) to work — in production.
One forward-deployed engineer, embedded in your stack, owning the outcome from discovery to production. Weeks, not quarters.
Book a deployment →