A small team covering the whole business.

Pascal is a Brisbane based business advisor and serial entrepreneur. He has built businesses in both Europe and Australia, and has been through the full cycle more than once: starting them, growing them and selling them. Advice on exits and growth comes from having done it with his own companies, not from a textbook.

His background is in performance marketing and business growth, years of running paid search and social campaigns where the only measure that counted was return on spend. That discipline shapes how the whole practice works.

He is the first point of contact for new clients, and from the first review onwards the work is a team effort: every plan is built with growth, numbers and legal thinking in it from the start.

Chris handles the data and systems side of the practice: analysis, dashboards, reporting and code optimisation. His work turns scattered spreadsheets and slow tools into a live view of the business.

He reviews the software businesses actually run on, from ecommerce platforms to internal tooling, and either tunes it or replaces it. Because he writes code himself, recommendations come with working solutions, not just findings.

Lindsay is a commercial intellectual property and corporate lawyer with deep experience across design, manufacturing, technology, supply chains and the creative industries. He sits on the Queensland Law Society Technology and Intellectual Property Law Committee.

His approach matches ours: proactive rather than reactive, practical advice rather than lengthy letters, and long term relationships rather than one-off transactions. Legal services are provided through an independent incorporated legal practice, coordinated within your overall advisory plan.

Uriah has spent more than twenty years in enterprise technology, building and scaling technology practices internationally. He implements AI and data systems for organisations ranging from local businesses to global enterprises in aerospace, energy and healthcare.

His rule is the same one the whole practice runs on: AI goes where it pays for itself. Data gets unified first, use cases get ranked by return, and what gets built goes into production and gets measured, not parked as a pilot.