Deep dives into AI agents, cloud infrastructure, and the future of software engineering.
Securing AI Systems: A Practical Guide to AI Security AI systems introduce new attack surfaces that traditional security approaches don't address. Protecting your AI investments requires understanding these unique vulnerabilities. The AI Attack Surfa...
AWS vs Azure vs GCP: Choosing the Right Cloud for Your AI Workloads Selecting the right cloud provider for your AI infrastructure is one of the most consequential decisions you'll make. Each platform has distinct strengths, and the right choice depen...
Kubernetes for AI Workloads: A Practical Guide Kubernetes has become the de facto platform for deploying AI and machine learning workloads. But running ML on Kubernetes requires understanding its unique requirements. Why Kubernetes for AI? 1. Scalabi...
Document Automation with AI: From Manual Processing to Intelligent Extraction Every organisation drowns in documents. Invoices, contracts, medical records, applications—the paperwork never stops. Traditional approaches to document processing are slow...
The True Cost of Cloud: Understanding Your AWS, Azure, and GCP Bill Cloud bills have a way of surprising people. What started as a few hundred pounds a month quietly becomes thousands—then tens of thousands. Understanding where your money goes is the...
Infrastructure as Code: Why Your Cloud Setup Should Be Version Controlled If your cloud infrastructure isn't defined in code, you're operating with unnecessary risk and inefficiency. Infrastructure as Code (IaC) has moved from best practice to essent...
Building AI Assistants That Actually Help: Lessons from Enterprise Deployments Everyone's building AI assistants. Most of them are terrible. After deploying conversational AI solutions across healthcare, manufacturing, and professional services, we'v...
From Proof of Concept to Production: The AI Deployment Gap Here's an uncomfortable truth: most AI proof-of-concepts never become production systems. Industry research suggests 87% of AI projects fail to reach deployment. Not because the technology do...
RAG vs Fine-Tuning: Choosing the Right Approach for Your LLM Application You want an LLM that knows your business. But how should you customise it? Two main approaches dominate: Retrieval Augmented Generation (RAG) and Fine-Tuning. Each has strengths...
Why Your Business Needs Custom AI Software in 2025 The AI landscape has evolved dramatically. While ChatGPT and other general-purpose AI tools have democratised access to artificial intelligence, businesses are discovering that generic solutions ofte...
