The engineering architect of PRAXIS — a proprietary programme intelligence platform live in production on a Neo4j knowledge graph with AI governance built into its operational core.
PRAXIS — Production Intelligence
PRAXIS is a live production system that governs programme delivery in real time — tracking tasks, dependencies, milestones, and governance constraints across a Neo4j knowledge graph that maintains structural integrity automatically. The AI advisory layer (METIS) reads programme state from the graph and provides governance-aware recommendations that respect the 99 automated constraints.
PRAXIS is simultaneously the practice's own delivery infrastructure and the live demonstration of Systematic AI architectural principles. Every engagement the practice runs is governed through PRAXIS — the methodology is running software, not a slide deck.
Engineering at Principal Level
Daniel's role eliminates the gap that undermines most strategy-led practices: the distance between architectural intent and production reality. When the practice designs an architecture, Daniel builds it. When a client engagement requires technical delivery, Daniel leads it. There is no handoff to a delivery team that did not participate in the design — because the designer is the builder.
This is the structural answer to the practice's core proposition: strategy through delivery without handoff. Daniel is the reason that proposition is credible at the technical layer.
Systematic AI Architecture
Daniel's engineering capability extends across the full Systematic AI stack — Knowledge Graph design and implementation, GraphRAG integration, agentic AI orchestration, and LLM integration. The architectural principles the practice advocates are principles Daniel has implemented in production, not principles borrowed from vendor documentation.