Insights
Product, design, AI, and engineering perspectives from our team.
API-First Architecture: Why It Matters for AI Readiness
API-first architecture creates the foundation for seamless AI integration by making business data programmatically accessible. Learn practical patterns for retrofitting APIs onto legacy systems and designing interfaces that scale with AI demands.
Modernising .NET Legacy Applications: A Practical Migration Path
.NET Framework modernisation is critical for Australian enterprises, but the challenge is doing it without breaking production systems. The strangler fig pattern offers a safe, incremental approach to migrate legacy applications to modern .NET 8.
From AI Pilot to Production: Scaling Your Proof of Concept
Most AI pilots never reach production deployment due to the gap between proof of concept and operational readiness. Learn how to bridge this gap with proper infrastructure, monitoring, and team planning.
AI Consulting Pricing Models in Australia: A Guide for CTOs
Understanding the three main AI consulting pricing models—fixed price, time and materials, and retainer—helps CTOs choose the right commercial approach for different project types and risk profiles. The key is matching pricing structure to project uncertainty and organisational needs.
How to Evaluate RAG System Quality: Metrics That Actually Matter
Comprehensive guide to evaluating RAG system quality in production. Learn essential metrics for retrieval precision, answer faithfulness, and operational performance to ensure reliable AI-powered applications.
Scaling AI Pilots to Production: The Technical Reality in Australia
Moving from AI pilot to production requires more than scaling up—it demands different architecture, skills, and processes. Most pilots skip the infrastructure and operational complexity needed for real-world deployment.
Vector Database Architecture for RAG Applications in Australia
Vector databases form the backbone of RAG applications, but selecting the right architectural approach requires understanding trade-offs between managed services, open source solutions, and PostgreSQL extensions. Australian organisations must also consider data sovereignty and compliance requirements when making these decisions.
Building Production-Ready AI Systems: Our Development Approach
Learn how Horizon Labs builds production-ready AI systems with comprehensive MLOps, vendor independence, and business-centric strategies. Our approach ensures AI solutions that work reliably in the real world.
Build vs Buy vs Partner: AI Adoption Paths for Mid-Market
Mid-market companies face a critical choice when adopting AI: build custom solutions in-house, buy off-the-shelf SaaS tools, or partner with specialists. Understanding the trade-offs in cost, speed, control, and risk helps you make the right decision for your specific context.