AI & Automation Consultant · Certified Management Consultant · 12+ years strategy + build
Most people who call themselves AI consultants can show you a slide deck. I can show you systems I've shipped — AI agents, self-hosted automation infrastructure, and human-in-the-loop workflows running real business processes. I work AI-augmented: I architect, review and ship fast because I pair deep solution judgement and op-sec with modern AI tooling. Outcomes are the proof. Below are short walkthroughs — each covers the problem, what got automated, where the human stays in control, and the stack.
Setting up a new client's automation environment meant hours of manual server, security and software setup — slow, and every manual step is a chance to get something wrong.
A tool that builds the entire environment automatically from a single setup file — one command instead of a checklist.
A full day of setup collapses to minutes — identical every time, with security built in from the start.
A single declarative YAML config drives the whole provision. The tool spins up a Hetzner Cloud server, points DNS through Cloudflare and triggers Let's Encrypt SSL via Traefik, hardens the box, generates per-environment secrets and stores them in Bitwarden, then deploys the service layer through Coolify using custom Docker Compose templates.
Core services deployed end-to-end: Uptime Kuma (monitoring), Baserow (database), DocuSeal (document signing) and self-hosted n8n (automation). Idempotent and repeatable — the same config reproduces the same stack, and secrets never touch the config file or version control.
Hetzner · Coolify · Cloudflare DNS/SSL · Traefik · Bitwarden · Docker Compose · n8n
Teams want AI to handle incoming requests, leads and tickets, but can't risk it sending the wrong thing to a customer on its own.
A workflow where AI reads each request, sorts it, and drafts the reply — then stops and waits for a person to approve, edit or reject before anything goes out.
The repetitive reading and drafting is automated; a human keeps the final say — saving hours of triage a week without losing control.
An n8n workflow triggers on inbound items (email/form/webhook). An LLM node classifies intent, urgency and topic; a switch routes by classification — low-risk items down an automated path, sensitive/high-value items to a manual queue. The LLM drafts a response, then the flow halts at a human-in-the-loop approval node (approve / edit / reject) before any send action fires.
Every run logs the AI's proposal and the human's decision, giving a clean audit trail. Constrained prompts and scoped credentials keep the model from taking unilateral action.
n8n · LLM API · REST/JSON · switch routing · HITL approval gate · audit logging
People make decisions off dashboards every day — but a dashboard is only as trustworthy as the maths behind it, and most can't show that the maths is correct.
A live tracking dashboard with the key numbers up top, and an automated test suite that checks every calculation behind them.
Decisions made on numbers that are verified, traceable and trustworthy — not just numbers that happen to look right.
Vanilla ES-module single-page app, no build step. The calculation logic (e.g. NAV and tax/CGT maths) lives in pure, isolated modules with no DOM or network coupling, which is what makes it unit-testable. JSON files act as the versioned data layer; writes are atomic across multiple files with auto-snapshot logging.
A harness of 150+ inline tests runs against the pure modules so every displayed number is provably correct, not just plausible. Served by a lightweight Python static server with optional write endpoints.
vanilla ES modules · pure-function math modules · JSON store · atomic writes · Python static server · 150+ tests
For many organisations the blocker to using AI isn't capability — it's that they can't send sensitive data to an outside AI service.
Custom AI agents that complete real multi-step tasks, running on an AI model hosted locally — plus deliberately limited access, so an agent can only do what it's allowed to.
The same AI capability, but the data never leaves the building — AI you can put in front of a compliance team.
Two purpose-built agents (OpenClaw, Hermes) explore goal decomposition and tool use — given an objective, the agent plans steps and calls only the tools it's explicitly granted (deliberately scoped, least-privilege access rather than open-ended control).
Runs against a locally-hosted LLM (GLM 5.2) on local hardware, so sensitive data never leaves the machine — solving the data-sovereignty blocker that stops many organisations adopting AI. Same capability as a cloud API, without the data egress.
AI agents · local LLM (GLM 5.2) · scoped tool access · on-prem / data-sovereign
Before the AI builds, the discipline. The same process mapping, requirements (BRS), UAT/production rigour, regulatory delivery and senior-stakeholder engagement is exactly why my automation ships and survives in production — not just in a demo.
A major bank had overlapping trading systems and complex tax-reporting obligations spread across many business units — costly, risky and hard to manage.
Merged three trading systems into one, moved core financial data onto a single modern platform, and automated regulatory (FATCA/AEOI) reporting across five business units — working with senior IT, finance and business leaders.
Lower cost, less duplication, and regulatory reporting that runs reliably — delivered through proper requirements, testing and production rollout.
Consolidated three derivative trading systems (Murex Energy, Front Arena) into a single Murex GTS platform; migrated/replicated a Basel II data mart into SAP HANA as part of a cross-country UK|SA delivery team toward a unified financial architecture.
Delivered FATCA/AEOI/SARS IT3 reporting standardisation across 5 business units — vendor scoping, as-is/to-be analysis, gap analysis, data mapping and data-dictionary artefacts. Ran full SDLC (BRS, technical & interface-design specs, UAT, production cutover, training) in SAFe 4.0 with Kanban/JIRA, including EXCO planning with IT, Finance and Business.
Murex · Front Arena · SAP HANA · Basel II · FATCA/AEOI · BRS · UAT · SAFe 4.0 · JIRA
During COVID, multiple government departments needed to understand how ready they were for new technology and the changing world of work.
Ran a Fourth Industrial Revolution (4IR) readiness assessment across several government bodies, plus feasibility studies, large-scale surveys and executive research reports.
Clear, evidence-based readiness findings and recommendations that senior public-sector decision-makers could act on.
Delivered a Fourth Industrial Revolution (4IR) readiness assessment across multiple government bodies — SETAs and state/national departments — during COVID. Designed and ran large-scale questionnaires/surveys for industry-report building (Gartner/Cognizant-style), plus feasibility studies for large government initiatives.
Produced executive-grade research reports and led senior stakeholder engagement across departments. Delivered under the MB Consulting banner for client Redflank.
4IR readiness · survey/questionnaire design · feasibility studies · industry reports · executive engagement
Resume, references (including Australian referees), and a live walkthrough available on request.