AI Infrastructure

From GPU Infrastructureto Enterprise AI.

From GPU data center build-out and operations to AI inference infrastructure — bloomax helps enterprises adopt AI at the right scale, from the ground up.

Services

AI Infrastructure, Three Ways

bloomax delivers GPU-powered AI infrastructure in three forms — from small-scale proof-of-concept environments to dedicated clusters and fully managed operations, tailored to your needs and scale.

Public Cloud GPU
01 / Public Cloud GPU

Public Cloud GPU

GPU computing environments tailored to development and validation workloads. Contact us to discuss configurations, availability, and pricing.

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02 / Private AI Cluster

Private AI Cluster

A dedicated GPU cluster environment designed around your workload requirements — delivering stable inference and training in a fully private setup.

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Private AI Cluster
Managed AI Factory
03 / Managed AI Factory

Managed AI Factory

bloomax handles everything from infrastructure build-out to day-to-day operations, so your team can focus entirely on AI workloads.

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OUR ROLE

Clarifying the path from concept to deployment.

bloomax's Role

Adopting AI in business operations or services requires more than provisioning GPUs — it means thinking through the right configuration for your use case, how data will be handled, and how the infrastructure will be operated after deployment.

bloomax helps customers clarify what they want to achieve and what their infrastructure needs to support, then works with them to plan a path to deployment. We combine GPU cloud, dedicated GPU clusters, and build-and-operate support — and coordinate with technology partners where needed — to propose an approach suited to your use case and scale.

You are welcome to reach out even if you are not yet sure where to start.

Customer

Goals, business requirements, existing environment

bloomax

Requirements clarification, configuration proposal, deployment coordination, role definition

Technology Partners

Equipment, products, and specialist services as needed

Coordination structure and responsibilities are defined on a per-project basis.

01

Clarify use case and requirements

We start by understanding the business or service you want to enable with AI, your expected usage volume, budget, and timeline. We also look at how much of your existing systems and infrastructure can be leveraged, and what data handling requirements apply.

You do not need to have a fully defined specification at the outset. We help separate what is known from what still needs to be confirmed, so you can move toward a decision with clarity.

Key topics

Use case / Scale / Budget & timeline / Existing environment / Data handling

02

Evaluate configurations for your use case

Whether you are starting with small-scale development and validation or need a dedicated environment for ongoing workloads, the right infrastructure depends on your use case and volume.

bloomax evaluates not just GPUs but also network, storage, and operational requirements. We present options in a way that lets you compare performance, cost, and scalability.

Key topics

GPU configuration / Network & storage / Cost / Scalability / Operational overhead

03

Support the coordination needed for deployment

Even after a configuration is agreed upon, there are items to confirm before deployment can proceed — supply terms, timelines, and scope of responsibility.

bloomax coordinates with technology partners as needed and helps clarify what the customer is responsible for, what bloomax will support, and what partners will provide.

Key topics

Supply terms / Deployment schedule / Build scope / Stakeholder coordination

04

Define operational responsibilities before deployment

AI infrastructure requires ongoing monitoring, maintenance, incident response, and configuration review after deployment. We confirm before deployment which areas the customer will manage internally and where support is needed.

bloomax helps define the scope of build and operational responsibilities in line with the services used and the customer's own operational capacity. Support terms and coverage are discussed individually.

Key topics

Monitoring & maintenance / Incident escalation / Updates & changes / Operational scope

Building on this work, bloomax is also preparing Token Factory — an AI inference service for enterprise use.

Specific scope, team structure, costs, and schedules are discussed individually based on your requirements and contract terms.

Discuss the right approach for your organization
Deployment Guide

Where do you start with AI infrastructure?

Use case, scale, output quality, data handling, cost and operations — five key points to clarify before evaluating AI inference infrastructure.

Useful even if your requirements aren't finalized yet.

Read the guide

GPU selection, dedicated environment setup, operations review — see example consultation scenarios.

View consultation examples
bloomax Token Factory | Coming Soon

From GPU Infrastructure to Enterprise AI Inference.

Where Managed AI Factory handles GPU cluster build-out and operations, Token Factory is the next step — aiming to deliver inference APIs and dedicated inference environments. We are building this service to support enterprise AI adoption.

GPU Data Center

GPU Data Center Planning,Deployment & Operations

From requirements assessment to deployment and operations, bloomax supports GPU data center projects for AI and simulation workloads.

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bloomax team
Careers

We're Hiring — Join Our Team

Explore our open roles and apply through our careers page.

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Contact

Talk to Us About AI Infrastructure

Whether you have a specific requirement or are still exploring options, we are happy to discuss GPU infrastructure, data centers, and AI inference at any stage.

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About

Company Overview

Company

bloomax Inc.

CEO

Shinjiro Ono

Founded

December 12, 2012

Address

Tennozu Bay Tower, 13F East A, 2-3-12 Higashi-Shinagawa, Shinagawa-ku, Tokyo, Japan