Four ways to work with us,
that fit together.

Service one

AI products

For a workflow you already understand, where building from scratch would mean reinventing something proven.

Aether, our platform, holds working product components for common business workflows: document drafting, operational search, structured reporting, and others. Rather than starting a build from a blank page, we configure one of these against your data, your terminology and your systems.

Configuration still means real work: connecting your systems, checking outputs against how your team actually operates, and training your people to use it well. What it does not mean is paying to build something that already exists in working form elsewhere in our practice.

• Configured against your existing systems and data
• Grounded in your own content and terminology
• Deployed in weeks, not a full build cycle
• Same security and governance as a custom build
• Priced for configuration, not development
• No obligation to buy more platform than the workflow needs

See what Aether gives you →

Service two

Data as a Service

For organisations whose data is the actual blocker.

Most of the companies we meet run somewhere between ten and thirty separate systems. Making a decision means bouncing between them, and the value of the data only shows up once it is together in one place.

We design, deliver and then operate a lakehouse for you. It is built on Azure and Databricks, it stays in Australian regions, and it is charged as a service rather than as a large upfront platform project.

• Lakehouse architecture and delivery
• Ingestion from ERP, CRM, files and sensors
• Transformation and data quality monitoring
• Governance, lineage and access control
• Reporting and self-service analytics
• Managed, co-managed, or build and transfer

Service three

Custom development PODs

For a solution particular enough that no existing product or platform component fits.

We start with your people and your process, not the technology. What does the work look like today, where does it slow down, what decisions are hard, and what would people do differently if the information were in front of them. Only then do we talk about a solution.

A POD is a focused team, not a rotating cast: a solution lead, engineers, and whoever the problem needs, working your use case from definition through to production. We build it with your team rather than for them, so the knowledge stays in the building and your people can run it once we go. If you would rather we kept operating it, that is a decision you make at the end, not one baked in at the start.

• Data and AI readiness assessment
• Use case identification and prioritisation
• Solution architecture and design
• Build and integration with your systems
• DataOps, MLOps and LLMOps once it is live
• Handover, documentation and support

Service four

Staff augmentation

For teams that have the roadmap and need more hands, not more advice.

Hiring data and AI engineers is slow and expensive, and a permanent hire is the wrong shape for a six month gap. Our specialists embed inside your team, in your tools and your process, working to your priorities rather than ours.

• Embedded engineers, full or part time
• Data, AI, cloud and platform specialists
• Working inside your tools, your process and your standards
• No minimum term beyond what the engagement needs
• Reporting to your priorities, not ours
• Advisory and coaching for internal teams