Insights
Product, design, AI, and engineering perspectives from our team.
From Spreadsheets to Data Infrastructure: A Migration Path
Many growing Australian companies still run finance and operations reporting on spreadsheets long after they've outgrown them. This guide covers the signs it's time to move, what a first data infrastructure build should include, and how to sequence the migration without disrupting month-end.
AI-Augmented Test Automation for Legacy Modernisation
AI-augmented test automation uses machine learning to generate, maintain, and prioritise software tests — a genuine accelerant for legacy modernisation, but not a substitute for human judgment on test intent. This piece sets out where AI-generated tests are reliable, where human review stays essential, and how to structure a testing strategy around both.
MLOps Consulting: What Australian Mid-Market Teams Actually Need
Enterprise MLOps advice rarely fits a mid-market team running a handful of models with a small data team. Here's what a right-sized MLOps consulting engagement covers — minimum viable stack, build-vs-buy tooling, team shape, and a maturity model.
Agentic AI vs RPA: Workflow Automation for Professional Services
RPA breaks the moment a contract, ledger discrepancy, or compliance document doesn't fit the script. Agentic AI handles the judgment-heavy, exception-prone work in between — with human approval gates and audit trails built in, not bolted on.
AI Consulting Melbourne: How to Evaluate an AI Consultancy
Evaluating an AI consultancy in Australia comes down to a few concrete questions: who actually does the work, do they have production deployments, and can they speak to Australian Privacy Principles compliance. This guide gives business leaders a practical framework for assessing fit, asking the right questions, and understanding how mid-market AI engagements are typically structured.