Financial Services
For banks and regulated enterprises
Japan-resident GPU compute and LLM platforms for FSA-supervised organizations — contractual audit rights, per-workload FISC documentation, zero-persistence inference, and a single JPY invoice.
Solutions
Every layer of AI — from dedicated hardware to a hosted API
Five products on one platform: run your own GPU servers, bring your containers to a managed platform, open a ready-made AI lab, deploy a private LLM, or simply call an API. All deployed, operated, and supported in Japan.
Product catalog
Five products, one foundation
Every product runs on the same Japan-based platform. Start with one — and grow into the next layer when you are ready.
Compute
GPU Bare Metal
Your own dedicated servers
Your own dedicated GPU servers, in data centers across Japan — the raw engines of AI, reserved just for you.
AI Platform
Your containers, our operations
Bring your containerized jobs — our platform runs them on the discounted Flexible tier or the Production tier, managed with Kubernetes.
Research Environment
A ready-to-use AI lab
A ready-to-use AI lab: JupyterLab notebooks, optimized environments, one click — no setup, no IT project.
LLM Services
LLM as a Service
Your own private LLM, with an API
Deploy any open-source LLM with one click on your own scalable GPU environment and get an API for production. It is your system — completely isolated, shared with nobody.
LLM API Endpoint
An OpenAI-compatible API for open models
An API just like OpenAI's or Claude's — for open-source models. Fixed shared performance, pay per token. Official OpenAI & Anthropic models are also available on a single JPY invoice.
Not sure where to start?
Tell us what you want to do — we will map it to the right product in one conversation.
Compare
Five products, side by side
Every product through the same three questions — what it is, when it fits, and how it bills.
| Product | What it is | Usage scenario | Billing responsibility |
|---|---|---|---|
| GPU Bare Metal | Your own dedicated GPU servers in data centers across Japan. | You need dedicated hardware with full control for your own stack. | Per node, by the hour or day |
| AI Platform | Managed platform running your containerized jobs on Flexible and Production tier Kubernetes capacity. | You run your own workloads — on the discounted Flexible tier or the Production tier. | Tiered, usage-based |
| Research Environment | One-click JupyterLab AI lab, ready in under 60 seconds. | Experiments, prototyping, team collaboration. | Environment included, GPU usage metered |
| LLM as a Service | Your own dedicated open-source LLM deployment with a production API. | Private, isolated LLM for regulated data, with your own scaling. | Per GPU-second, with limits you set |
| LLM API Endpoint | Shared OpenAI-compatible API for open-source models — official frontier models via reseller. | Fast integration, agents, customer-facing apps. | Per token |
- What it is
- Your own dedicated GPU servers in data centers across Japan.
- Usage scenario
- You need dedicated hardware with full control for your own stack.
- Billing responsibility
- Per node, by the hour or day
- What it is
- Managed platform running your containerized jobs on Flexible and Production tier Kubernetes capacity.
- Usage scenario
- You run your own workloads — on the discounted Flexible tier or the Production tier.
- Billing responsibility
- Tiered, usage-based
- What it is
- One-click JupyterLab AI lab, ready in under 60 seconds.
- Usage scenario
- Experiments, prototyping, team collaboration.
- Billing responsibility
- Environment included, GPU usage metered
- What it is
- Your own dedicated open-source LLM deployment with a production API.
- Usage scenario
- Private, isolated LLM for regulated data, with your own scaling.
- Billing responsibility
- Per GPU-second, with limits you set
- What it is
- Shared OpenAI-compatible API for open-source models — official frontier models via reseller.
- Usage scenario
- Fast integration, agents, customer-facing apps.
- Billing responsibility
- Per token
Platform differentiators
What the products are built on
Two capabilities engineered into the platform itself — not bolted on afterwards.
Green Orchestration
Workloads are scheduled dynamically around renewable energy cycles — lowering carbon impact and cost at the same time, without changing how your teams work.
AI Commons
A marketplace where idle compute capacity is shared and monetized. Reserved capacity earns value when your teams are not using it — and the ecosystem becomes more efficient for everyone.
Not sure which product fits?
Tell us about your workloads, data requirements, and compliance constraints. A senior member of our team will help you map the right path — within one business day.