Insights
Product, design, AI, and engineering perspectives from our team.
The Real Cost of AI Implementation in Australia: Budget Guide
AI implementation costs in Australia range from $25,000 for simple chatbots to $500,000+ for complex systems. Here's transparent pricing across discovery, build, and operations phases, with real budget ranges by project type.
Building Production RAG Systems: Beyond the Demo to Reliable Scale
Most RAG demos work beautifully with perfect documents and cherry-picked queries. Production RAG systems face messy reality — document diversity, edge cases, and 99%+ accuracy expectations that require systematic engineering across chunking, embedding, retrieval, and monitoring.
How to Implement AI in Your Business: A Guide for Australian Companies
A comprehensive implementation guide for Australian businesses looking to adopt AI. Covers the complete journey from discovery through operations, including team structure, budget planning, and regulatory considerations.
On-Device AI for Mobile Apps: When Edge Beats Cloud
On-device AI processes machine learning directly on mobile devices, delivering sub-100ms response times and offline functionality. This guide covers Core ML, TensorFlow Lite, model optimisation, and real-world applications for Australian mobile development.
The Strangler Fig Pattern: Modernise Legacy Apps Without Rewrites
The Strangler Fig pattern lets you modernise legacy applications gradually by routing traffic to new services while keeping old systems running. This approach reduces risk compared to complete rewrites while delivering value incrementally throughout the migration process.
AI Agents That Work: Architecture Patterns for Multi-Agent Systems
Multi-agent AI systems are becoming production reality for Australian enterprises, but most implementations fail due to poor architecture choices. Learn the orchestration patterns, communication protocols, and error handling strategies that separate proof-of-concept demos from production-ready systems.
The Mid-Market AI Readiness Guide: 5 Things to Fix Before You Build
Most mid-market companies rush into AI implementation without addressing fundamental readiness issues. This practical guide covers the five critical gaps that distinguish successful AI implementations from expensive failures — from messy data reality to missing success metrics.
How to Choose an AI Consultancy in Australia: 8 Key Questions
Choosing an AI consultancy is fundamentally different from hiring traditional software developers. Here are eight critical questions to evaluate AI consultancies before you sign, covering IP ownership, production metrics, data infrastructure, and Australian compliance requirements.
AI Consulting vs In-House: When to Outsource vs Build Your Team
Choosing between AI consulting and building an in-house team depends on your timeline, budget, and strategic priorities. Most successful AI adoptions use a hybrid approach: consultants for initial development and knowledge transfer, followed by internal teams for ongoing evolution.