Insights
What We Learned Testing Five Sensitive Data Detection Tools
We tested sensitive data detection tools Amazon Macie, Microsoft Purview and three open source tools on 18,049 documents to see how much sensitive data automated data classification really finds. Read for our recommendations and what a layered approach costs to run.
The missing foundations holding back AI in energy and utilities
AI adoption is accelerating across energy and utilities, yet many initiatives never progress beyond experimentation. Writing in Energy Manager Magazine, Mark Simpson explains why proprietary data, targeted use cases and explainable governance matter more than model capability when it comes to scaling AI in critical infrastructure.
Cutting Code AFK. How Ralph Wiggum can do the work for you
So it finally happened, I was pulled into a meeting and told to replace myself with AI.” Read Elena’s full breakdown on how to use the Ralph Wiggum Loop to speed up development, including learnings and a step-by-step guide.
The reality of sovereign AI: How to avoid dependency without building everything yourself
Ben Saunders, Co-Founder of WeBuild-AI, writes for Silicon Valleys Journal on why sovereign AI is about control and optionality, not building every model in-house, and how a multi-model control plane reduces vendor lock-in.
The AI-Native SDLC eBook
A comprehensive guide to what the software development lifecycle looks like now that AI agents are part of the team, and how to implement it at enterprise scale.
Why most AI strategies fail before they scale
Mark Simpson, Co-Founder of WeBuild-AI, writes for EnterpriseTalk on why AI tools spread while adoption stalls, and why outdated workflows and change management, not a skills gap alone, block AI strategies from scaling.
The real barrier to AI in financial services isn't regulation but trust
Ben Saunders, Co-Founder of WeBuild-AI, writes for The European Financial Review on why most financial services firms use AI in some form yet struggle to reach production, and why organisational confidence and accountability matter more than regulation alone.
Why will out-of-the-box AI fail in energy and utility operations?
Mark Simpson, Co-Founder of WeBuild-AI, writes for Energy Sustainability Solutions on why energy and utility AI programmes stall in pilot, and why generic models fail without connected operational data, domain context, and governance on critical infrastructure.
Why the future of AI in banking depends on trust, not trials
Ben Saunders, Co-Founder of WeBuild-AI, contributes to The Fintech Times on why banks stall after proof of concept, and why scaling AI in banking is an operating-model and trust problem, not only a regulatory one.
Metrics for AI projects - what your team feels versus what the board wants to see
Your team can feel the time an AI tool saves, while your board needs to see where that time actually went. Here’s what to measure, and what an invoice pipeline taught me about the difference.
The Knowledge Graph Tool Inside Our AI Accelerator
Why we paired Neo4j, knowledge graphs and the Model Context Protocol inside our AI Accelerator, and how the combination turns months of integration work into days.
The confidence gap holding back AI in financial services
Ben Saunders, Co-Founder of WeBuild-AI, writes for Finance Derivative on why financial institutions struggle to turn AI pilots into measurable outcomes, and why internal confidence, governance, and stakeholder alignment matter as much as compliance.
WeBuild-AI Named an OpenAI Select Partner
WeBuild-AI announces its new partnership with OpenAI. WeBuild-AI will continue working with OpenAI to help organisations build, deploy, and scale AI solutions responsibly and effectively at a global scale.
Why aligning tech to real world operations will unlock AI's potential
Mark Simpson, Co-Founder of WeBuild-AI, writes for The AI Journal on uneven UK AI adoption, why investment alone does not create business value, and what operational alignment, data foundations, and governance require before AI scales.
AI Maturity in UK Electricity Networks
Every electricity network operator is working with AI; fewer can say where AI projects actually stand, what's stalling progress internally, or how they compare with peers working under the same regulatory constraints. This report answers that using data from operators across the UK electricity system, not vendor commentary or generic industry predictions.
