Business
What we do
Three layers, bottom-up, covering what it takes to put AI into a business. Each can be engaged on its own, but designing coherently across all three is where our value concentrates.
AI INFRASTRUCTURE
Compute, matched to the pace of the business.
Design, build and operation of GPU clusters, plus dedicated capacity on hourly or monthly terms. From high-density power and cooling through scheduler and storage selection to full SRE operations.
- Training queues are long enough that the research cycle no longer turns
- GPUs were purchased but utilisation is low and depreciation has no clear path
- There is no internal basis for deciding between on-premise and cloud
- Operations staff cannot be hired, and incident response depends on one person
INFERENCE PLATFORM
Delivering models in a usable form.
An LLM gateway consolidating multiple large language models behind one endpoint, inference optimisation, token cost visibility and chargeback, fine-tuning, and evaluation infrastructure.
- Separate AI contracts have proliferated by department, with no view of total spend or actual usage
- You want to switch models but cannot estimate the engineering cost on the application side
- Inference cost has overrun the budget and usage caps are the only remaining lever
- Accuracy dropped after a model update and nobody can say which part regressed
APPLIED AI
Never stop at the PoC.
Operational AI agents, RAG platforms for Japanese-language documents, MLOps / LLMOps adoption, AI strategy and ROI modelling, internal guidelines, and capability transfer.
- The PoC succeeded but production ownership and procedures were never settled
- You want internal document search but permissions and disclosure risk remain unresolved
- Dependence on external vendors persists and no knowledge accumulates internally
- Leadership has never been given a basis on which to decide the investment
Bring us in while it is still an idea.
The most common questions we receive are "how many GPUs should we buy" and "should we own or rent". We welcome conversations long before requirements are settled.