RankSaga · AI-Driven Decision Software

CLASSIFICATION POSTURE · RESIDENCY-CONTROLLED

DEFENCE · GOOGLE CLOUD

Google Cloud, designed for the residency posture defence work requires.

We build and operate AI-enabled software on Google Cloud for defence-adjacent and government customers. Vertex AI, Gemini-class model integration, Anthos hybrid topologies, and assured workloads, designed for residency, sovereignty, and the operational constraints of regulated environments.

Google Cloud's strength for defence-adjacent work is the model surface and the hybrid story. The decisions that matter are residency, identity, and the boundary between Google-operated infrastructure and the customer-controlled environment.

Vertex AI · GeminiModel surface
AnthosHybrid + on-prem topologies
Residency-ControlledRegion selection + assured workloads
Audit-FirstCloud Audit Logs + customer-controlled SIEM

PRACTICE OVERVIEW

GCP for the defence-adjacent customer.

Google Cloud is the third hyperscaler we run customer workloads on. For defence-adjacent and government customers, agencies running mission-adjacent workloads, prime contractors with parts of a programme on GCP, partner-nation customers with a Google-aligned platform strategy, there are real reasons GCP is the right call. The Vertex AI surface is genuinely strong; Gemini-class models are competitive on the workloads our customers care about; and the Anthos hybrid story is the cleanest of the three hyperscalers when part of the deployment has to live outside the cloud entirely.

Our GCP practice is staffed by engineers who treat residency as the starting constraint. Region selection, Australian regions for Australian customers, or partner-nation regions where the customer's residency posture requires, is the first decision. Identity integration with the customer's enterprise directory, customer-managed encryption keys across every boundary that touches sensitive data, and assured-workload-equivalent controls are designed in from week one rather than added in a hardening sprint.

The AI surface in most engagements is a mix of Vertex AI for hosted Gemini-class models, customer-fine-tuned models served on Vertex Endpoints with private networking, and open-weight models running on GKE or Anthos for workloads that require single-tenant serving. Where the deployment is hybrid, part on GCP, part on-premise, part inside an enclave, Anthos is often the connective tissue that makes the topology workable.

We are pragmatic about hyperscaler choice. Most of our reference defence work runs on sovereign Microsoft Azure. GCP is offered where the customer's residency posture, partner-nation arrangements, or model surface preferences make it the right call. The engineering discipline is the same; the configuration changes.

WHAT WE DO

GCP for defence-adjacent work, by the surface we touch.

01 / Capability

Vertex AI & Gemini

Integration of Vertex-hosted Gemini-class models into mission applications, with customer-managed keys, private networking, and customer-controlled audit. Model selection driven by residency posture and workload fit, not by vendor preference.

02 / Capability

Customer-Fine-Tuned Models

Vertex Endpoints with private networking for customer-fine-tuned models, and GKE-hosted serving for open-weight models running inside customer-controlled clusters where single-tenant serving is required.

03 / Capability

Anthos Hybrid Topologies

Hybrid deployments where part of the workload runs on GCP and part runs on-premise or inside an enclave. Anthos as the connective tissue, with a documented boundary posture between the cloud and the customer-controlled tier.

04 / Capability

Residency & Assured Workloads

Region selection, project topology, identity integration, and key management designed for the customer's residency posture and assured-workload-equivalent controls.

05 / Capability

IAM, KMS, and Audit

Customer-managed encryption keys via Cloud KMS, IAM policy aligned to the customer's authorisation model, and Cloud Audit Logs configured for accreditation-grade evidence with SIEM integration into the customer's security operations.

06 / Capability

Operations Inside the Project

Embedded engineers operating the deployment alongside the customer's platform team, capacity, model lifecycle, patching, incident response, and continuous hardening of the GCP surface.

OPERATING MODEL

Residency first. Build inside it. Operate continuously.

GCP engagements follow the same forward-deployed model we run elsewhere, adapted to the specifics of GCP project topology, the Vertex AI surface, and the Anthos hybrid story where it applies.

01 / Step

Region & Residency Posture

Region selection, Australian regions, partner-nation regions, or assured-workload arrangements, and residency architecture are the first decisions. Project topology, identity integration, and key management are designed against the customer's residency posture before workloads land.

02 / Step

Build Inside the Posture

Application surface, mission software, Vertex AI integration, Anthos hybrid components, operator UI, is built and deployed inside the residency-controlled posture. Working software in operator hands within weeks, against the production controls.

03 / Step

Embedded Operations

We stay deployed. Patching, model lifecycle, capacity, incident response, and the continuous hardening of the GCP surface, alongside the customer's platform team for as long as the engagement requires.

POSTURE DETAIL

How we configure GCP deployments for defence-adjacent work.

Region

Region choice driven by the customer's residency posture: Australian regions for Australian customers; partner-nation regions where required; assured-workload-equivalent arrangements where the customer's framework requires them.

Project Topology

Multi-project organisation with explicit boundaries between identity, security, audit, and workload projects. Folder hierarchy and organisation policies aligned to the customer's authorisation model.

Network

Shared VPC architecture with explicit egress controls, Private Service Connect for Google service access, and a documented boundary posture reviewed against the customer's residency requirements.

Identity & Access

Cloud Identity / Workspace federation with customer's enterprise directory, IAM with permission-boundary equivalents, and role-based access into the workload aligned with the customer's authorisation model.

Key Management

Customer-managed encryption keys via Cloud KMS, including External Key Manager (EKM) where the customer requires keys held outside Google entirely.

Audit & Logging

Cloud Audit Logs with customer-controlled retention and export, application-layer logs into customer-managed aggregation, and SIEM integration consistent with the customer's security operations posture.

Hybrid

Anthos for hybrid topologies where part of the workload runs outside GCP, including connection to on-premise infrastructure or to an enclave that holds the most sensitive tier of the application.

POSITIONING

Where GCP fits, in our defence practice.

Our reference defence deployment is on sovereign Microsoft Azure with an air-gapped operating environment. GCP is an adjacent capability we offer where the customer's residency posture, model surface preferences, or hybrid topology make GCP the right call.

  • ·Vertex-hosted Gemini-class model integration into mission applications.
  • ·Customer-fine-tuned models on Vertex Endpoints with private networking.
  • ·Anthos hybrid topologies for partly-on-GCP, partly-elsewhere deployments.
  • ·Residency-controlled architectures designed for accreditation review.

QUESTIONS

GCP for defence-adjacent work, in practice.

How does GCP compare to sovereign Azure for Australian defence workloads?+

Sovereign Azure has the deeper Australian government engagement and broader sovereign-region service availability. GCP is competitive on the model surface, Gemini-class models, and is sometimes the right call where the customer's residency posture, partner-nation arrangements, or hybrid topology aligns better with GCP than Azure. We work on both; we recommend honestly per workload.

Can you run Anthos on-premise or in an enclave?+

Anthos clusters run on customer infrastructure. For hybrid deployments where part of the workload runs on GCP and part runs on-premise, Anthos is often the cleanest connective tissue. For fully-disconnected enclaves we typically recommend non-Anthos topologies, see our air-gapped deployment capability.

What models can run on Vertex AI for our defence workload?+

Vertex-hosted Gemini-class foundation models, customer-fine-tuned variants of those, and customer-uploaded open-weight models served on Vertex Endpoints with private networking. Where the workload requires that the model artefact never leaves customer-controlled infrastructure, we host on GKE or Anthos rather than Vertex.

Are you US-authorised on FedRAMP for GCP?+

No. As with AWS, our GCP work is aligned with Australian and partner-nation frameworks. For US-authorised GCP defence workloads we partner with US-authorised primes who hold the relevant accreditations.

How do you handle keys?+

Cloud KMS with customer-managed keys for every encryption boundary that touches sensitive data. Where the customer requires keys held outside Google entirely, External Key Manager (EKM) so the key material lives in a customer-controlled HSM.

ENGAGE

If GCP is the right cloud for your defence-adjacent workload, the residency posture should be engineered like it.

We design GCP deployments for accreditation review and operate them continuously. If you are running, or planning to run, defence-adjacent or government workloads on GCP and need an engineering team that takes residency and identity seriously, we should talk.

ENGAGE

Bring us in on the problem before it has a name.

We work best when we are embedded early, alongside the team that owns the mission, the data, and the operational risk. Government, commercial enterprise, or defence: if your environment is regulated, sensitive, or air-gapped, that is where we are most useful.