BigQuery analytics
Warehouse models, partitioned tables and scheduled queries feeding dashboards in Looker or other BI tools.
Cloud platforms
GCP development.
Google Cloud is strong in data analytics, container platforms and AI, with BigQuery and Vertex AI as standout services. We use it for analytics-heavy products and AI work, particularly alongside Gemini.
A short call. Your first build, a fixed quote, and the timeline. No obligation.
What we build with GCP
Where it fits.
Vertex AI pipelines
Training, evaluation and deployment of models with managed endpoints and pipelines.
Cloud Run services
Containerised APIs that scale to zero, with Pub/Sub triggers and Secret Manager for configuration.
GKE clusters
Kubernetes workloads on GKE with autoscaling, workload identity and Terraform-managed networks.
When it is the right choice
Choose GCP when
- →Analytics at scale is the core of the product.
- →You use Gemini or Vertex AI models.
- →You want simple, container-first deployment with Cloud Run.
Worth knowing
Honest trade-offs.
- →The service catalogue is smaller than AWS, so some niche needs require third-party tools.
- →Product names and tiers change over time, so we confirm current options when designing.
Often paired with
BigQueryVertex AICloud RunTerraformPub/SubLooker
Related services
Services that use it.
Proof
Work built by the same team.
Closeum
13+ connected modules from calls through commissions
13+connected modules
5role types
32completed transactions
40+leads managed
SIIMS
Orders, production, warehouse, and dispatch on the same records
4operational roles
37backend tests passed
17hosted workflow tests passed
Ledgerline
603 tests passed in a dated financial-control verification
SAR 760Kcash reconciled end to end
603tests passed
14control findings fixed
3finance sources in one ledger
Common questions
Before you start.
When is GCP better than AWS?
When data analytics or Google's AI services are central. For general hosting, the differences are smaller and your team's skills decide.
Can you migrate us to GCP?
Yes. We inventory workloads, plan the order of moves and run old and new in parallel before cutover.
Is BigQuery suitable for real-time data?
It supports streaming ingestion, which suits near-real-time analytics. Strict low-latency lookups are better served by an operational database.
What do you build with GCP?
Data warehousing, Vertex AI, Application hosting, Analytics, and related work. We choose GCP when it is the right fit for the product, the team and the budget.
Can you work with our existing GCP code?
Yes. We can review what you have, fix what is fragile, and extend it, or build alongside your team.
Keep exploring
More than GCP.
Where we apply it
The Audit
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