Insights
From the Lab
Practical perspectives on AI engineering, deployment, and strategy from our work with enterprise clients.
When AI Makes Sense: A Framework for Enterprise Decision-Making
Not every problem needs AI. We share our evaluation framework for determining when machine learning adds genuine value versus when simpler solutions suffice.
Building Reliable AI Systems for Defence Applications
Mission-critical environments demand a different approach to AI deployment. Lessons learned from building systems where failure is not an option.
The Hidden Costs of AI Projects: What Nobody Tells You
Beyond compute and talent, AI initiatives carry costs that rarely appear in business cases. A realistic look at total cost of ownership.
Computer Vision in Healthcare: Augmenting, Not Replacing, Expertise
How we designed diagnostic assistance tools that enhance clinician decision-making while maintaining full accountability and transparency.
From POC to Production: Closing the AI Deployment Gap
90% of AI projects never make it to production. We examine the technical and organisational factors that determine success.
Data Quality Over Data Quantity: Building Effective Training Pipelines
In our experience, curated datasets consistently outperform larger, noisier alternatives. A practical guide to data-centric AI development.