Services

Consulting and productised architecture

I work with organisations that need clarity, governance and delivery around complex systems: AI, data, integration and enterprise applications. Below are typical engagement shapes that can be tailored or productised for your context.

Consulting

Architecture consulting engagements

Architecture vision & roadmap

Define where you are, where you’re going, and how to get there without losing control.

  • Architecture Vision Document (baseline, target, principles, risks)
  • Business, data, application and integration architecture views
  • Traceability from requirements to architecture work packages

Integration & application modernisation

Move from fragile point-to-point integrations and monoliths to resilient, observable architectures.

  • Application inventory, capability mapping and technical debt analysis
  • API-first, event-driven and microservices decomposition
  • Migration strategies involving ESBs, legacy and cloud iPaaS

ML/Agentic AI architecture

Turn AI ideas into production-grade solutions with clear boundaries, governance and cost control.

  • LLM, tools (MCP), RAG and vector DB architecture
  • Azure AI Search, OpenAI and observability patterns
  • Data residency, security and compliance considerations
Productised

Repeatable solution offerings

Architecture governance starter kit

A lightweight, practical governance model that fits Agile delivery and your existing teams.

  • Architecture Review Board design and operating model
  • Minimal, effective artefacts and decision records
  • Templates for standards, patterns and reference architectures

Integration blueprint for HR & Finance

A reference architecture for integrating HR and Finance platforms (e.g. Workday, ADP, Dayforce, Snowflake, NetSuite).

  • Canonical data flows and integration patterns
  • Batch, API, event and streaming patterns per use case
  • Monitoring, observability and cost management guidance

GenAI on low-code platforms

A pattern for embedding GenAI into low-code environments (e.g. Salesforce, D365) safely and effectively.

  • Use case discovery and prioritisation
  • Architecture for secure AI integration
  • Governance and monitoring for AI features