When meaning is explicit, every answer traces back to the facts and rules that produced it. I help organizations build that foundation in open W3C standards they own, so their AI can show its work.
A model can only be faithful to meaning it was given, and most organizations never wrote theirs down; it lives in schemas, spreadsheets, and the heads of the people who built them. So the answers sound right and can’t be checked, and every change still costs a rebuild.
Make that meaning explicit and the system can tell you what it knows, how it knows it, and what follows from it that nobody ever typed.
Large firms can’t scale ingenuity, so they scale a playbook. I start with the problem in front of you and build the answer around it. The first hour is on me.
Book your free hour →Your organization already has an ontology; it’s implicit in the systems you run. I lift it out and make it explicit, so the model starts from production reality rather than committee decisions, and nothing you’ve invested in gets rebuilt from scratch.
Only open W3C standards, with no vendor lock-in. RDF, OWL, SHACL, and JSON-LD outlive any tool, vendor, or model release, and I have no platform to sell you.
Semantic projects tend to stall between the demo and production, where meaning meets architecture. I wrote Mastering Software Architecture (Apress, 2025) and I’m writing The Semantic Blueprint (Packt, 2027), so one person designs both sides, and your proof of concept is built to survive production from the first day.
Pick the shape of help that fits the problem. If you’re not sure yet, start with the first one.
Your AI is underperforming or unreliable. I’ll show you where it hits the semantic ceiling, and what it takes to break through.
The ceiling is the point where a model stops knowing and starts guessing.
Read Chapter 1, “The Semantic Ceiling” →A trusted advisor, on call.
Strategy, and a second opinion before the decision that’s hard to reverse. Includes reviews: an outside read of your architecture, your model, or your AI plans, with findings you can act on.
A rapid proof of concept: a fast, safe way to explore.
Sized to answer one real question on your own data, in days rather than months. You see what a semantic layer can do for you before you commit to building one.
From proof of concept to production: where knowledge lives, who owns it, and how it’s governed.
The decisions that are expensive to reverse get made deliberately, before production makes them for you, and the model can change without breaking what depends on it.
Workshops on your own systems, so the exercises become the real thing.
Hands-on, from half a day to two days, in the semantic layer, software architecture, and API design. Your people leave able to teach it to their teams.
Your team builds it alongside me, and keeps it.
Hands-on learning with high-fidelity knowledge transfer: your people at the keyboard, on your own schema and data, in daily sessions. Everything they learn is applied immediately, and what they build becomes the foundation of your enterprise-wide semantic layer.
Whatever the shape, you own everything we make.
Public workshops run through semantic.training.
Bring the idea you can see but can’t quite name yet. That’s the right time to talk.
Let’s go somewhere interesting.