Nine practices.
One thesis.
Enterprise AI fails in predictable places: an unclear portfolio, an unusable data estate, a system of record nobody can integrate with, and a governance model that arrives after the lawyers do. Our practices exist to close those gaps in the order they actually block you — which is usually not the order you expected.
AI Strategy & Consulting — Where AI actually has leverage in your value chain, scored honestly, sequenced, and costed.
Project Management Consulting — PMO design for discovery-led work, embedded programme leadership, recovery, and benefits realisation the CFO signs.
Agentic AI Solutions — Multi-agent systems wired into your systems of record, with evaluation harnesses, human checkpoints, observability, and rollback.
AI Automation & Governance — A live control plane: model inventory, risk classification, evaluation gates in CI/CD, and audit evidence generated as a by-product.
Data Analytics — Modern data platforms, a governed semantic layer, and analytics engineering that produces numbers everyone trusts.
BI & Visualisation — BI designed around the decision, not the dataset — plus estate rationalisation and conversational analytics.
Digital Transformation — Mainframe migration and legacy modernisation executed incrementally, with the business running throughout.
Data Migration — Zero-loss migration with semantic mapping, automated reconciliation, lineage preservation, and rollback at every gate.
Cloud Migration — The 7 Rs applied honestly, per application. Landing zones, FinOps, resilience, and a service architecture that does not turn into a distributed monolith.