Solutions
Clinical AI agents come first — delivered on private model infrastructure and a multi-region compute platform we operate ourselves. Three integrated capabilities, one accountable partner for medical institutions of every size.
Medical Agent Co-Creation
Together with university and hospital partners, we build AI agents specialized for real clinical practice — grounded in local guidelines, evaluated against local standards, and shaped by the professionals who will use them.
Our co-creation model pairs your clinical and research expertise with our platform engineering: joint definition of use cases, iterative evaluation on curated datasets, and a governance framework that keeps every output reviewable. The objective is a durable, locally governed capability for medical AI — safe, reliable, and controllable.
- Joint research and development programs with academic partners
- Human-in-the-loop by design: agents support, clinicians decide
- Evaluation harnesses and Japanese clinical benchmarks
- Clear boundaries: workflow support, not autonomous clinical decisions
Private Clinical LLM Platform
Agents are only as trustworthy as the models beneath them. We deploy open-weight large language models — including leading model families from China and Europe, alongside Japanese-language models — on infrastructure that your institution controls. No patient data is ever sent to an external API.
Models are selected and evaluated per workload, adapted to local clinical language — with deep strength in Japanese — and served from dedicated GPU capacity: on-premises within the hospital, in a private data center, or in an isolated cloud environment under your governance.
- Model selection, evaluation, and clinical-language adaptation, including deep Japanese capability
- Retrieval-grounded answers over your guidelines, protocols, and documents
- Air-gapped and fully offline deployment options
- Comprehensive audit logging and role-based access control
- Managed operations: monitoring, updates, and versioned model rollouts
Distributed Compute Fabric
Reliable AI for healthcare cannot depend on a single facility. We build and operate clustered GPU infrastructure across Japan, Malaysia, and Thailand, orchestrated as one fabric — a design driven by four practical realities:
- Power: metropolitan Japan faces acute data-center power constraints; regional sites unlock capacity
- Cost: training and batch workloads run where energy and operations are most economical
- People: a follow-the-region operations model deepens staffing resilience
- Resilience: geographically separated sites provide genuine disaster recovery
Data-residency tiering is enforced at the scheduler level: patient-identifiable workloads remain in-country — or on-premises — while de-identified training and batch jobs are placed where capacity and cost are optimal.
A measured path from pilot to production
Healthcare adoption succeeds in stages, not leaps. Our engagement model is designed for institutional review processes and clinical governance.
1 · Assessment
Joint scoping of use cases, data sensitivity, and governance requirements with your clinical, IT, and compliance teams.
2 · Pilot
A contained, privately hosted agent pilot on real workflows — measurable, reviewable, and reversible.
3 · Production
Hardened rollout with audit logging, access control, staff enablement, and integration into institutional systems.
4 · Operation
Continuous monitoring, model evaluation, and versioned upgrades — operated with you, not just for you.
Scope an agent pilot for your institution
Tell us about your environment and objectives — we will propose a measured, governance-first path to a working pilot.