The opportunity, on one page.
For capital, channel partners, and organisations considering a deeper relationship with Newcastle Rising. Strategic position, moat, what we're building, what we're looking for — direct and unvarnished.
Custom AI applications for professional services — running locally, data protected.
Every other AI company in most cities resells OpenAI, Anthropic, or Microsoft. Their offering is an API key and some configuration. The client's data goes to US servers. The vendor has no technical moat and no switching cost. We do the opposite: we build custom AI-powered applications for professional services firms, run them against a frontier AI backend co-located in the client's city, and manage the whole system as a fixed-cost monthly service. The data never leaves the client's jurisdiction. The applications are built specifically for their workflows — their documents, their templates, their way of working. Every month the system is used, switching cost grows. The position — custom apps, local AI, data protected — is structurally unaddressable by US cloud providers and technically unreachable by local IT support companies.
Four players who cannot fill this position.
US hyperscalers (AWS, Azure, GCP)
They need cloud dependency — that is the product. They cannot offer "data stays in your city" without dismantling their own architecture. The sovereign pitch is structurally unavailable to them.
Generic cloud AI SaaS (Harvey, Clio, etc.)
Multi-tenant US cloud infrastructure. Built for the average customer in a vertical — not for any specific firm's workflows, precedents, and templates. Cannot offer genuine data sovereignty.
Local IT support companies
Have the client relationships but not the technical capability to deploy frontier AI, build custom applications, or manage inference infrastructure. They are a channel, not a competitor.
In-house AI teams
Costs £80,000–£120,000 per year in salary for one engineer. Still requires infrastructure, application development, and ongoing model management. Only viable for large organisations.
Server-level unit economics are strong and predictable.
| Item | Detail |
|---|---|
| One production server | ~$20,000 hardware, co-located at $300/month |
| Clients per server (shared tier) | 5–8 clients at $2,000–$3,000/month each |
| Monthly revenue per server | ~$15,000 (5 clients at $3,000) |
| Monthly costs | ~$500 (colo, power, misc) + ~$550 hardware amortisation |
| Net margin per server per month | ~$14,000 |
| Additional servers | Largely self-funding within 2–3 months of filling capacity |
The managed service fee is the base. Implementation fees ($30,000–$100,000 per client) and development retainers ($5,000–$15,000/month) add on top. A single mid-size law firm can generate $136,000 in year one revenue.
Three shapes of useful relationship.
IT managed service providers
MSPs already serving law firms, accountancies, and healthcare clinics have the client relationships but no AI capability. A revenue-share arrangement works cleanly: they bring the client, we build and manage the AI, both parties win. This is the fastest route to market in any city.
Strategic equity
Aligned investors who understand the sovereign AI thesis, the managed service model, and regional Australian positioning. Not looking for spray-and-pray; looking for two or three partners who'll be useful. AUD-denominated structures preferred.
Government, council, university
Hunter-region institutional partners — local council, NSW Government departments, University of Newcastle. Pilot deployments, joint funding into regional digital infrastructure, advocacy for Hunter as a credible AI hub.
Email Matt directly.
No deck required, no warm intro needed. Two paragraphs of context — who you are, what kind of relationship you're considering — is enough to start. We respond inside one business day.