Industry 01 · Healthcare & Life Sciences
Health data systems that clear compliance and scale.
From HIPAA-regulated clinical platforms to drug-development pipelines on HPC clusters, we build healthcare software where privacy, auditability, and correctness are load-bearing requirements — not afterthoughts.
What we build
From intake to insight, with compliance at every layer.
Compliance engineering
HIPAA and NIST-aligned architectures: access controls, encryption, audit trails, and the documentation that gets you through review.
Healthcare data management
Ingestion, storage, and governance for clinical and research data — designed so the right people see the right data, provably.
Drug development platforms
Computational research pipelines and data platforms for discovery teams — including GPU and HPC workloads that don't fit the public cloud.
Data de-identification
PHI/PII de-identification pipelines supporting Safe Harbor and expert-determination workflows, so research data can move without risk.
Research collaborations
Engineering partnership for academic and clinical research groups — turning lab-grade code into systems reviewers and IT departments accept.
Cloud & HPC for life sciences
Regulated-workload environments on AWS, GCP, Azure, or on-prem OpenStack HPC — sized and secured for genomics-scale data.
Compliance posture
Built for the audit you haven't scheduled yet.
Every healthcare system we deliver ships with its compliance story written down — controls mapped, decisions justified, evidence collectable.
- Encryption everywhere — in transit and at rest, with managed key rotation.
- Complete audit trails — who touched which record, when, and why.
- Least-privilege access — role-based controls mapped to your org structure.
- Environment isolation — production PHI never leaks into dev or test.
- De-identification by default — research and analytics run on de-identified data unless explicitly authorized.
Proof in this vertical
Related case studies.
Healthcare & Life Sciences
MCP
tool-layer governance · NIST-aligned
A governed agentic interface for exploring sensitive health datasets
A conversational agent over sensitive health datasets whose every capability is an explicit, permission-scoped tool — from exploration to ML inference, with humans holding the last word.
T-CAIREM — Medical AI · 2025 — present
Healthcare & Life Sciences
256
clinical fields · abstracted on-prem
Abstracting 256 clinical fields from PHI charts — without the data leaving the building
A DAG-decomposed abstraction pipeline running fine-tuned sub-30B models on two in-house H100s. Every field auditable; PHI never leaves hospital-controlled hardware.
T-CAIREM — Medical AI · 2025 — present
Healthcare & Life Sciences
04
regions · one federated platform
Health Data Nexus: a federated platform for sensitive health-data research
Compute-attached research notebooks over governed health data, federated across the US, Canada, Korea, and Africa — LMS-gated access, hybrid GCP + SciNet sovereign compute, and HIPAA/PHIPA egress guardrails enforced in code.
University of Toronto — T-CAIREM · 2022 — present
Healthcare & Life Sciences
100%
serverless
A serverless platform for exploring MEG and EEG brain data
A MEG/EEG exploration and analysis platform a two-person startup team can operate — Lambda to SageMaker, all CloudFormation.
Cove Neurosciences · 2022 — 2023
Working with regulated health data?
Tell us where the data lives, who needs it, and what's blocking you. We've probably met your constraint before.