Proof that sovereign AI operations work in practice. Every capability described here is operational and demonstrable — not a prototype, not a roadmap item.
The most rigorous test of any platform is whether you would run your own business on it. We do.
Building a technology company requires capabilities across engineering, marketing, legal, finance, operations, and strategy. For a lean team, the traditional choice is either hiring extensively or relying on a patchwork of SaaS tools — each with its own data policies, vendor lock-in, and integration overhead. We needed a way to operate with the output of a much larger organisation while maintaining complete sovereignty over our data and processes.
We deployed Foundry as our operational core from day one. Every business function — from drafting legal documents and financial models to generating marketing content, analysing markets, and managing infrastructure — runs through the platform. Specialist AI agents handle domain-specific tasks within governed boundaries, while the three-tier autonomy model ensures that routine operations execute automatically, sensitive actions pause for review, and critical decisions always require human approval.
M-Suite replaced our dependency on third-party productivity tools entirely. Email, documents, calendaring, and collaboration all run on sovereign infrastructure under our control. No data leaves our environment unless we explicitly direct it to.
Specialist agents deployed across engineering, legal, finance, marketing, operations, and strategy
AI providers orchestrated simultaneously — Anthropic, OpenAI, Google, and xAI — with intelligent routing
Sovereign operations — zero third-party SaaS dependencies for core business functions
M-Suite applications replacing vendor-locked tools — email, docs, spreadsheets, calendar, and more
Autonomy model governing every AI action — autonomous, supervised, and commanded operations
Operational monitoring via OVERWATCH with morning briefs, standing orders, and situational awareness
AI governance is not a constraint — it is an enabler. By establishing clear boundaries, risk tiers, and approval workflows, we actually increased the speed and scope of AI deployment. Teams trust the system because they understand exactly what it will and will not do autonomously.
Multi-model orchestration eliminates vendor dependency. When one provider experiences degraded performance, tasks automatically route to alternatives. When a new model launches with superior capabilities in a specific domain, we add it to the fleet without disrupting operations.
Sovereign infrastructure is practical, not just principled. Running M-Suite on our own infrastructure was not significantly more complex than configuring SaaS alternatives — and the operational benefits (data control, customisation, no per-seat licensing) compound over time.
We are currently working with organisations across regulated industries. These case studies will be published as engagements conclude.
A regulated financial institution deploying Foundry to govern AI-assisted compliance monitoring, client communications, and risk assessment — with full FCA audit trail requirements met from day one.
A law firm using governed AI operations for document review, contract analysis, and legal research — with privilege-aware access controls and matter-level data segregation ensuring client confidentiality.
A healthcare organisation leveraging Foundry for clinical documentation support, administrative automation, and research analysis — with NHS DSPT compliance and patient data sovereignty maintained throughout.
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