Blog

You ask an AI a question (ChatGPT or other - they're all as guilty as one and other) and it replies instantly with something that sounds like it came from a well read expert who also happens to be polite, structured, and suspiciously confident. It's fluent. It's tidy. It even gives you bullet points. And then you discover one awkward detail. It is wrong.

We’ve all spent the last 18 months talking about “AI for customer service” like it’s a magic trick. Better bots. Smarter assistants. RAG for everything. And yet… handle times barely move, recontacts creep back up, agents still ask in Slack: “Which article is actually correct?” It’s not that the AI is bad. It’s that we’re asking it to reason on top of knowledge that’s fundamentally broken. Messy, contradictory, duplicated, outdated, scattered across Confluence, SharePoint, Se

"Ontology is lining up to be the buzzword of 2026" I'm hearing that everywhere now, but really? Palantir’s rise has put ontological modelling back in the spotlight – their Foundry platform is built on it. Microsoft is now moving ontology into Fabric. The race is on. It makes sense. Ontologies give generative AI something it desperately needs: grounding . LLMs are brilliant at pattern-matching and language, but terrible at enforcing logic. They’ll happily smooth over contradi