Case Studies

A selection of representative engagements. In keeping with our confidentiality commitments, institutions are described only in general terms; the value of each use case is what matters.

Private LLM Platform Documentation

Private LLM platform for clinical documentation support

A national university hospital in Western Japan

Situation

Clinicians faced a growing documentation burden — discharge summaries, referral letters, and insurance-related paperwork — while institutional policy ruled out sending any patient information to external AI services.

Approach

Open-weight LLM deployed on dedicated, privately operated GPU infrastructure
Drafting agents grounded in institutional templates and document conventions
Full audit logging; every draft reviewed and approved by the responsible clinician

Value delivered: clinicians gained a governed drafting assistant that reduces time spent on routine documentation while keeping patient data entirely within the institution's control — establishing a template for broader clinical AI adoption.

Agent Co-Creation Evidence Retrieval

Grounded evidence-retrieval agent for a research division

A medical research institute, Kansai region

Situation

Research staff spent substantial time searching guidelines and literature across Japanese and English sources, with no reliable way to verify the provenance of AI-generated answers.

Approach

Retrieval-grounded agent over curated guideline and literature collections
Every response traced to its source passages for immediate verification
Co-designed evaluation set with the institute's own researchers

Value delivered: researchers obtain sourced, reviewable answers in minutes rather than hours of manual search — and the evaluation methodology created jointly now anchors the institute's broader AI adoption discussions.

Private LLM Platform Patient Communication

Multilingual drafting support for international patient services

A regional acute-care hospital group

Situation

Growing numbers of international patients strained a small coordination team: discharge instructions and explanatory materials needed to be accurate, plain-language, and consistent across languages.

Approach

Privately hosted multilingual models with institutional terminology controls
Draft-translate-review workflow — coordinators approve every outgoing document
Consistent phrasing aligned with the group's communication policies

Value delivered: the coordination team can serve more international patients with clearer, more consistent materials — while sensitive information remains on infrastructure the hospital group controls.

Compute Fabric Resilience

Multi-site compute foundation for institutional AI programs

An academic medical consortium

Situation

A consortium's AI ambitions were constrained by metropolitan power availability, single-site risk, and the cost of premium domestic capacity for non-sensitive workloads.

Approach

Tiered workload placement: sensitive inference in-country; de-identified training and batch workloads across regional sites
Unified orchestration and monitoring across all locations
Geographically separated disaster-recovery posture

Value delivered: the consortium gained a credible path to scale AI research and services without compromising data residency — with better economics and genuine resilience against single-site failure.

Note: Institutional names, departments, and identifying details are withheld under confidentiality commitments. Reference conversations can be arranged under NDA — please contact us.

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