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AI Projects

I don't just advise on AI. I build with it.

The best technology advice comes from people who build. These are AI products and frameworks I've designed and shipped — from governance tools for enterprise retailers to live consumer products and autonomous project management for startups.

Retail & Commerce · Framework & Process Design

AI Capability Matrix & Governance Framework

For retailers evaluating and adopting AI responsibly

The problem

Most retailers know they should be doing something with AI. Very few have a structured way to evaluate where it creates genuine value versus where it introduces risk. The gap between vendor promises and operational reality is wide.

What I built

A structured capability matrix that maps AI use cases against business readiness, data maturity, and governance requirements. Paired with a governance process that gives leadership teams confidence to move forward without exposing the organisation to regulatory or operational risk.

How it works

  • AI use case scoring framework mapped to retail operating model
  • Data readiness assessment across customer, product, and operational domains
  • Governance process covering model risk, bias monitoring, and compliance
  • Board-ready reporting templates for AI investment decisions

The outcome

Gives retail leadership teams a clear, defensible path to AI adoption — knowing exactly where to invest, what to defer, and how to govern what they deploy.

Retail & Commerce · AI Product — Live

ProductMatch

AI competitive pricing intelligence for Australian retailers

The problem

Retail buyers and merchandisers make real pricing calls every week — on hero SKUs, on category resets, on sale events. The bigger retailers run this as a standing function with a BI team behind it. SMB and mid-market retailers make the same decisions on gut feel, not because their people are worse but because the analyst headcount isn't there and the tech team is heads-down on something else. The existing tools match on keywords and lie about confidence.

What I built

A self-serve SaaS that turns a product image into a defensible pricing recommendation in 90 seconds. Upload a SKU, ProductMatch finds visually similar products at Australian competitors using AI visual reasoning, fetches live prices, and produces a floor / sweet-spot / ceiling recommendation with the reasoning behind each number. Multi-tenant, multi-user, credit-based subscriptions, fully self-serve from signup to first scan.

How it works

  • Image-first input — no SKU spreadsheets, no integrations, no analyst on retainer
  • Multi-model AI pipeline: Claude Haiku for triage, Claude Sonnet for visual reasoning and similarity scoring, with extended-thinking recommendations
  • Live AU competitor coverage — Temple & Webster, Freedom, Amart, West Elm, Castlery, plus 40+ more, with no cached prices older than 24 hours
  • Built-in trust mechanics — similarity scores 0–100, human-in-the-loop corrections, full reasoning attached to every recommendation
  • Multi-tenant SaaS from day one: Clerk Organisations, Supabase RLS, atomic server-enforced credit ledger, Stripe-hosted Checkout and Billing Portal

The outcome

Live at productmatch.com.au since May 2026. v1 shipped in two weeks — full commercial loop including AI pipeline, multi-tenant auth, and Stripe billing — then iterated through polish and v2 using Claude Code, Claude Design, and a Linear-based planning discipline that treated every architectural decision as a documented artefact. The build itself became a case study in what AI-assisted product development looks like when the human stays in the architect's seat — and the working method now informs how I help clients build their own AI products.

Want this for your own product? Build with me

Financial Services · AI Product — Live

MyWealthTracker

AI-powered digital financial advisor

The problem

Australians navigating financial decisions face a fragmented landscape of tools and advice. Most digital finance tools are either too simplistic to be useful or too complex to be accessible. Professional financial advice is expensive and hard to access at scale.

What I built

A full-stack AI financial advisor built on current Australian tax law, superannuation rules, and financial planning frameworks. It provides personalised, regulation-aware guidance that adapts to each user's situation — not generic calculator outputs.

How it works

  • AI reasoning engine trained on current Australian financial legislation
  • Personalised advice generation across super, tax, investment, and insurance
  • White-label platform enabling mortgage brokers and financial planners to offer AI-powered guidance under their own brand
  • Lead generation engine that qualifies prospects before they reach a human advisor

The outcome

A live product serving real users, with white-label capability that turns financial advisors and mortgage brokers into AI-enabled practices — generating qualified leads while their clients get immediate, accurate guidance.

Startups & Scale-ups · AI Tool — Internal

AI Project Manager for Startups

Autonomous project governance across departments

The problem

Startups and scale-ups move fast, but fast without structure means projects stall, scope creeps, and teams lose alignment. Traditional project management tools track tasks but don't enforce discipline. Hiring a full-time PM for every workstream isn't viable at this stage.

What I built

An AI project manager that integrates directly with ClickUp and Slack to provide real-time project governance, status tracking, and intervention across multiple departments. It doesn't just track — it actively manages.

How it works

  • Deep integration with ClickUp for task, milestone, and dependency management
  • Slack-native interface for team updates, blockers, and escalations
  • Cross-departmental visibility — engineering, product, design, and operations
  • Governance engine that flags scope drift, missed dependencies, and resource conflicts before they become problems

The outcome

Teams ship faster with less overhead. The AI PM enforces the discipline of a seasoned project manager across every workstream, without adding headcount — purpose-built for the pace and constraints of startup and scale-up environments.

Professional Services · AI Agent — Live

Sally — Autonomous AI Practice Agent

AI infrastructure that runs a consulting practice

The problem

Solo consulting practices face a structural problem: the overhead of project management, context assembly, follow-up tracking, and client preparation consumes the same time regardless of firm size. What used to require a team of support staff either gets done slowly or doesn't get done at all.

What I built

An autonomous AI agent that operates as the operational backbone of my consulting practice. Sally lives in Telegram, manages project pipelines, scaffolds new engagements from a voice note, maintains persistent memory across every client interaction, and surfaces priorities before the first coffee. She doesn't wait to be asked — she operates continuously.

How it works

  • Telegram-native interface accessible from anywhere — phone, laptop, watch
  • Persistent memory that compounds across every engagement, conversation, and decision
  • Voice-to-structure pipeline: a single voice note becomes structured notes, task breakdowns, and routed follow-ups
  • Autonomous project scaffolding — "new project" creates a repo, board, and environment in seconds

The outcome

A solo consulting practice that operates like a product company. Clients get senior thinking with the responsiveness of a team — without the team. The gap between conversation and structured deliverable is hours, not days.

Why this matters

Advisors who build give better advice

When I advise a retailer on AI readiness, I'm drawing on the experience of having built and shipped AI products myself — not just evaluated other people's. When I assess whether an AI vendor's claims are credible, I know because I've built similar systems from scratch.

This hands-on capability is what separates practical advice from theoretical frameworks. Every project here involved real users, real constraints, and real decisions about where AI creates value and where it doesn't.

Building AI capability or evaluating where to start?

Whether you need a governance framework, a hands-on AI build, or just a clear-eyed assessment of what's possible — I've done all three. Let's talk about your situation.