EU AI Act High-Risk Audits: What to Have Ready by Q4
The EU AI Office began its first high-risk audits this month. The eight artefacts to have ready and the twelve-week plan we run with enterprise clients.
16 Enterprise AI articles on production outcomes, with lessons from real enterprise projects. Read the guides that fit your next decision.
The EU AI Office began its first high-risk audits this month. The eight artefacts to have ready and the twelve-week plan we run with enterprise clients.
Autonomous agents were the 2025 story. In 2026 enterprise teams are rebuilding them as deterministic workflows with LLMs as components. Here is our pattern.
A worked example of cutting enterprise LLM inference spend in 90 days with caching, routing and serving-tier changes, without downgrading the model.
Every enterprise now has more AI agents than it can name. Here's the governance layer we build before agent sprawl turns into an audit disaster.
Every enterprise AI programme reaches a point where direct model calls stop scaling. Here's the LLM gateway pattern we deploy, and why.
AWS, Azure or Google Cloud for enterprise AI? Compare GPU access, managed ML platforms, model choice, real costs and lock-in, with a clear verdict per cloud.
MCP has moved from spec curiosity to production infrastructure. What enterprises deploy, what they get wrong, and what good MCP looks like at scale.
A practitioner's playbook for controlling GPU and AI infrastructure costs at scale — the wasteful patterns we see most and the levers that move spend.
How we red team production LLM and agent systems for enterprise clients — the attack taxonomy that matters, our six-phase process, and where to invest first.
How to build an LLM evaluation framework for production: golden datasets, LLM-as-judge scoring, CI gates and live sampling that catch regressions early.
The enterprise AI trends that matter in 2026: what is delivering ROI, what is stalling and where budgets are moving, drawn from 500+ projects with real clients.
AI agents in 2026: what actually works in production vs. what's still vaporware. Tool-calling, orchestration patterns, and the enterprise guardrails that…
What does enterprise AI cost in 2026? Real ranges from a $15K proof of concept to $1M+ platforms, plus the hidden costs and how to scope a budget that holds.
85% of enterprise AI projects fail. We dissect the 5 root causes — poor data quality, missing MLOps, wrong team structure — and how to prevent each one.
Explore how AI is transforming enterprise cybersecurity. Learn about AI-driven anomaly detection, automated triage, and defending against adversarial AI.
Learn how to build a practitioner-led enterprise AI roadmap. Discover a step-by-step methodology for assessment, prioritisation, and phased rollout.
Book a free 30-minute call with us to identify quick wins and show you what's possible.