National AI capability built on coordination, not a national supercomputer — and independent of foreign model providers and their export controls. A route a sovereign lab can take today, at the cost of engineering.
Discuss a pilot or grantThe conventional route to frontier-class AI is to pretrain a frontier model: a fleet of 100,000+ accelerators, vast proprietary data, and one of the few-dozen world-class teams on Earth — billions of dollars and years of risk. The alternative most nations accept is dependence on foreign commercial labs, which means exposure to their pricing, their export controls, their data terms, and their strategic priorities. Neither is sovereignty.
Coordination, not compute. We orchestrate existing open models into frontier-class capability — and we've demonstrated it: a coordinated panel of free models beats the best single model by a statistically significant margin, on a standard public benchmark, scored against the objective answer key. Reproducible, auditable, and honest — every figure, limitation and negative result published. A capability a sovereign lab can field now, for the cost of engineering rather than a supercomputer.
No dependence on foreign labs, foreign infrastructure, or foreign export-control regimes. The capability is held domestically.
Capability scales with coordination design, not capital expenditure — frontier-adjacent results without a national-scale compute bill.
Open methodology, reproducible from public benchmarks and free models. Claims a procurement or oversight body can independently verify.
Not a proposal — a working proof of concept. The expensive uncertainty is already retired; scaling is an engineering and resourcing question.
For sovereign-AI programmes, grant bodies, and agencies evaluating domestic capability. Leave a contact and we'll arrange a technical briefing.