Senior AI expertise. Direct access. Real outcomes.

Feb 2026Why AI Startups Need a Different Kind of CTO, and What That Looks Like

AI-native startups fail when they hire traditional software CTOs who apply deterministic thinking to inherently probabilistic AI systems, creating a critical but overlooked leadership gap that costs companies months of misdirected effort.

Feb 2026The Investor's Technical Due Diligence Playbook: What Most AI Assessments Actually Miss

Current AI due diligence processes fail because they apply traditional software evaluation frameworks to fundamentally different AI risks, missing crucial questions about data provenance, model defensibility, and the intersection between technical depth and strategic positioning.

Feb 2026Best Consulting Firms for Defining Your AI Strategy in 2026: An Honest Buyer's Guide

This guide argues that choosing the right AI strategy consultant depends on matching your company's specific needs, size, and budget to the appropriate type of firm (whether global consultancies for enterprise credibility, specialist boutiques for technical depth, or independent consultants for focused expertise) rather than simply picking the most famous name.

Feb 2026The key metrics to measure the ROI of your LLM deployments

Most organisations measure LLM success using traditional software metrics whilst sitting on transformational cognitive infrastructure they barely understand how to evaluate properly.

Jan 2026EU AI Act Explained: Compliance Requirements and Business Impact

The EU AI Act's extraterritorial reach and risk-based classification system will reshape global AI development by creating competitive advantages for organisations that build regulatory compliance into their systems from conception rather than retrofitting it later.

Jan 2026Why Most AI Projects Fail Without Expert AI Consulting

Most organisations fail at AI because they mistake building models for building systems, burning millions on architectural decisions that doom projects from the start whilst ignoring the expertise gap that separates proof-of-concepts from production reality.

Jan 2026Building a Secure LLMOps Pipeline: From Development to Production

Most organisations treat LLM security like traditional DevOps while ignoring novel attack vectors through model weights, training data, and prompt injection that conventional tools cannot detect.