We help Australian businesses turn Google Cloud capabilities into useful everyday tools. From AI agents to knowledge search and connected workflows, we start with the work you want to improve.
Let’s talk about your ideaIndependent advice. Google Cloud is our primary build platform.
Cloud StorageApproved files
Gemini modelsAI capabilities
Cloud RunApps & integrationsGoogle Cloud brings AI models, application hosting and data services into one platform. We choose the parts your workflow needs and connect them to the tools you already use.
Bring Gemini models together with your business rules and carefully scoped tools. An agent could prepare a task brief, find the context for a request or propose the next step, with a person approving important actions.
AI agent developmentConnect approved documents and business information to an experience that helps people find answers. We design retrieval, source references and access checks together, so the answer can be checked against the information behind it.
Internal knowledge searchHelp your support team understand a request, find relevant guidance and prepare a response. The design includes clarification, escalation and a clear handover when the information is incomplete or a person needs to decide.
Customer service AIUse applications and integration services on Google Cloud to connect AI with existing software. We account for authentication, validation, unavailable systems and repeated requests, so a useful workflow has a dependable way to run.
System integrationsStill deciding where to start? Our AI strategy work helps you choose a worthwhile first project.
A team member asks, “How do I request access to a project?” An internal assistant finds the approved process, explains the steps and links to the source.
Cloud Run can host the application. Gemini models can help interpret the question and prepare a response using retrieved information. Approved files can be held in Cloud Storage or connected from a suitable existing source.
An illustrative design, using a fictional workplace question. Services, permissions and regional availability are assessed for each project.
Confirm the person’s identity and retrieve only information they are permitted to access.
Search maintained source material. Give the model relevant context and instructions for handling missing information.
Return clear steps and source links. If the guidance is missing or unclear, direct the person to the responsible team.
The assistant explains the process. It does not grant project access. An authorised person remains responsible for that decision.
A workflow map, source and access requirements, an outline architecture and cost assumptions. We agree the pilot scope and how to judge its usefulness.
One focused workflow tested with suitable examples, including unclear requests, restricted information and unavailable systems. Findings inform a decision to improve, expand or stop.
An agreed production setup, operating guidance and responsibilities. We plan monitoring, feedback and how to pause or recover the workflow when something needs attention.
A good build starts with clear expectations about systems, information, costs and responsibility.
Usually, a focused AI project can connect to systems you already use. We assess their APIs, access rules and commercial constraints first. Any proposed migration needs a clear business reason and an agreed scope.
An existing product may already meet the need. We compare its capabilities and licensing with your requirements before recommending a custom build. Custom work becomes useful when you need specific system connections, workflow rules, access controls or a different user experience.
Google Cloud offers Australian regions, including Sydney and Melbourne for Cloud Run. Data storage and AI processing are separate decisions: availability and residency commitments vary by service, model and endpoint. We check your requirements across the whole design, including connected systems, logs and backups. A global AI endpoint does not guarantee processing in Australia.
We map who can see each source and which actions each component may take. Cloud permissions, application access checks and human approvals work together. We test restricted access and failure cases, and agree how credentials, logging and retained information will be managed.
Cost depends on scope, integrations, data preparation and how the solution will be used. We separate delivery costs from ongoing model, hosting, storage and connected-service costs. A pilot uses explicit assumptions, appropriate alerts and usage controls, with costs reviewed before expanding. An alert alone does not stop spending.
We agree project access, billing, ownership of deliverables and operating responsibilities before the build. Where appropriate, the solution runs in your Google Cloud environment. Handover covers configuration, monitoring, routine changes and a named owner. Any ongoing support is scoped separately.
Yes. Bring one recurring task, the systems involved and someone who understands the work. We agree what a useful result looks like, test the approach with suitable examples and use that evidence to decide the next step.
The exact services depend on the project. These Google resources explain some of the building blocks and decisions behind the work.
Google Cloud product icons identify the technologies in the illustrative diagram. Product names and icons belong to Google.
Bring us the bottleneck, the big idea,
or the question you keep coming back to.