AI Advisory
& Integration.
From strategy to implementation — I help teams understand where AI adds real value, then build it into their stack. Not the hype. The architecture.
AI is a tool, not a strategy.
Most teams don't need more AI — they need the right AI in the right place. I work with organisations to cut through the noise: where does a language model genuinely save time? Where does automation eliminate repetitive work without introducing fragility? And where should you just leave things alone?
My approach starts with understanding your existing workflows, data, and team capabilities. From there, I design solutions that integrate cleanly into your stack — not bolted-on demos that fall apart in production.
Every engagement is different, but the approach is consistent: understand the problem, design the architecture, build it right.
AI Strategy & Roadmap
Where does AI fit in your organisation? I assess your workflows, data maturity, and team readiness to build a practical roadmap — not a slide deck that gathers dust.
LLM Integration
Custom integrations with OpenAI, Anthropic, and open-source models. RAG pipelines, function calling, structured outputs — built for reliability, not just demos.
Workflow Automation
Intelligent automation that connects your existing tools. Document processing, data extraction, content generation — the repetitive work your team shouldn't be doing manually.
Architecture & Infrastructure
The unglamorous but critical part: prompt management, model orchestration, cost optimisation, monitoring, and the guardrails that keep AI systems predictable in production.
What this looks like in practice.
I've built AI-powered invoice processing systems that handle thousands of documents monthly with near-zero error rates. I've designed MCP servers that give language models structured access to business data. I've helped teams move from 'we should use AI for something' to running production systems that genuinely reduce workload.
The common thread: every solution is built around how the team actually works, with clear fallbacks, proper error handling, and the kind of observability that lets you sleep at night.
Technologies I work with
LLM Providers — OpenAI, Anthropic Claude, local models via Ollama
Frameworks — Laravel, Python, Model Context Protocol (MCP)
Patterns — RAG, function calling, agentic workflows, structured outputs
Infrastructure — Vector databases, queue-based processing, cost monitoring
Let's figure out where AI fits.
No pitch deck, no generic recommendations. A real conversation about your workflows, your team, and what would actually help.
Get in Touch