Industries

Healthcare

Clinical data stays inside boundaries you own and audit.

Healthcare organisations need AI and automation without exposing protected health information to shared public models. We design systems where inference, storage, and access controls live inside your cloud environment — with encryption, logging, and operational runbooks your security team can stand behind.

What teams face

PHI cannot cross unclear boundaries

Consumer AI tools process prompts on shared infrastructure with terms unsuitable for clinical or patient data. Healthcare workloads need a clear data boundary auditors and privacy officers can trace.

HIPAA-aware architecture at scale

Compliance is an architecture problem: VPC isolation, KMS encryption, least-privilege IAM, and retention policies must be consistent across every service touching patient records.

Clinical workflows resist one-size-fits-all AI

Care gap analysis, clinical note summarisation, and operational automation each need different models, guardrails, and human-in-the-loop review — not a generic chatbot pasted onto EHR exports.

What we build

Compliant private AI pipelines

Clinical note analysis and operational AI running entirely within your AWS environment — no protected health information sent to third-party training pipelines.

Controlled access and audit logging

Role-based access, session logging, and data residency choices so clinical and operational teams get AI capability without losing oversight.

Secure platform engineering

Kubernetes, CI/CD, and observability built for healthcare uptime requirements — with encryption at rest and in transit as defaults, not exceptions.