▮ SI-1 · Superintelligence practice
Superintelligence has left the research lab and entered the policy vocabulary. We help organizations get ready for it: deciding where frontier AI pays for itself, building the systems that put it to work, and wiring in the safeguards that keep people in control.
// 01 · CAPABILITY MAP
Six modules, one board. Engage one, or wire them together: every module connects to the same core of evaluation, governance and human control.
Find where frontier and superintelligent systems change your operating model, your risk and your competition, and where they don't, before committing budget.
Agents that plan, act and use your tools and data, with guardrails, review gates and a complete audit trail of every step they take.
Deep-research and retrieval pipelines that compress weeks of analysis into hours, with every answer sourced, current and checkable.
Measure models before you depend on them: test sets built from your work, red-teaming, multi-model comparison and regression checks on every release.
The groundwork advanced AI depends on: collection, pipelines, warehouses, search indexes, model hosting and a realistic plan for compute.
Running it once it's live: monitoring, cost and latency control, human-override controls, incident response, and handover with runbooks.
// 02 · SAFETY INTERLOCKS
More capable systems need stronger controls. Every engagement ships with four interlocks, built into the architecture rather than written into a policy document.
Spend, scope and permissions are capped in the system itself, so a runaway process trips a limit instead of a budget.
Your data flows in to do the work, and never back out to train third-party models. Access is limited to what the job needs.
Every model or prompt change is scored against your test set. Regressions trip the watchdog before users ever see them.
People approve consequential actions, and a single switch takes the system offline. The off switch is tested, not assumed.
// 03 · SIGNAL PATH
Start where the evidence is. Most work begins with a short assessment or prototype and grows once there's proof it's worth it.
A fixed-scope assessment: your workflows, data and risks mapped against what frontier AI can do now and next, success defined in measurable terms, and a written recommendation at the end.
Discuss an assessment →The smallest version that can be tested on real inputs, with an evaluation set from day one and the safety interlocks wired in, then hardened for production alongside your team.
Discuss a build →Running, measuring and improving the system once it's live, as capabilities advance and models change, or a clean handover with documentation and runbooks.
Discuss operations →// 04 · DIAGNOSTICS
AI systems whose capabilities exceed expert human performance across a broad range of tasks. However quickly that arrives, the systems on the way there are already capable enough to change how organizations work. We help you get value from today's frontier systems while building the structures you'll need as they grow more capable.
Leadership teams, public-sector bodies and regulated organizations that need to make serious decisions about advanced AI, and engineering teams that need to ship it safely. Engagements run from a two-week assessment to building and operating a production system.
Whichever suits the task and your constraints: hosted models from the major labs, open-weight models on your own infrastructure, or a mix. Systems are designed so the model can be swapped as the frontier moves, without a rebuild.
It stays in the environments you approve, access is limited to what the work needs, and nothing is used to train third-party models. Specific security, residency and compliance requirements go into the statement of work.
Yes. Work can be delivered end to end or side by side with your engineers, with documentation and knowledge transfer built in, so you're never dependent on us to keep it running.
// 05 · OPEN A CHANNEL
Tell us what you're working on. The first conversation is about the problem, not a sales deck.
