Data & AI for healthcare and medtech, from raw data to production

We turn ad-hoc experiments into a repeatable, documented process: versioned data and models, tracked training runs, automated validation, deployment on your infrastructure, and monitoring that tells you when the model drifts before your customer does.

• Training pipelines, experiment tracking, data and model versioning
• Data catalog and lineage: which data, which sources, which demographics, answered in minutes
• Drift and performance monitoring, retraining workflows, change control for every release
• Documentation suitable for FDA and EU MDR reviewers and hospital security teams

Pipelines that ingest DICOM, FHIR/HL7, genomic and device streams into one governed platform: cataloged, de-identified where needed, and accessible to the people who need it, from R&D to finance.

• Lakehouse and pipeline architecture sized for medical imaging, not web clicks
• Interoperability with EHRs, PACS and partner systems through FHIR and DICOM standards
• De-identification and anonymization, including text burned into images
• Governance: who sees what, and proof of it when the auditor asks

Landing zones, migrations and production infrastructure on your own cloud account: encryption, logging, access control, backups and the documentation that turns a security questionnaire into a formality. HIPAA for the U.S., GDPR for Europe, one architecture for both.

• Migrations from a PaaS, on-prem or another cloud, planned around the clinicians using the product
• Infrastructure as code, so every environment is reproducible and reviewable
• Cost optimization: GPU scheduling and storage tiers tuned for medical workloads
• AWS is our default and deepest expertise: Select Partner programs, support and funding paths
• Other clouds and on-prem when that is where you are

When the model itself is the missing piece, we build it: imaging models validated against radiologists, document understanding for clinical and billing paperwork, voice agents that collect what matters, and agents that do repetitive work with a clinician or billing specialist in the loop.

• Medical imaging: segmentation, detection and classification (MRI, CT, X-ray, pathology)
• Clinical NLP and document AI: registries, coding, quality checks on medical records
• LLM assistants and agents grounded in your own data, with guardrails and review queues
• Data- and evaluation-driven validation; a clear answer when a model isn't good enough to release

A rare extension for an engineering partner: we help source consented patient data through clinical partners, anonymize it, and run labeling with the right tooling and medical oversight, so your team trains on what it actually needs.

• Data acquisition through hospital and clinic partnerships, with consent and ethics handled
• Labeling tooling built on 3D Slicer with our own backend; labeling protocols reviewed by a physician
• Dataset documentation ready for your regulatory file

For data teams at providers, labs and research organizations: integrate the systems, automate the reporting, then put the data to work: revenue cycle automation, registries that fill themselves, data products partners pay for. Every project starts with a business case in hours and dollars.

• Integrated reporting across sites, departments and systems: fewer manual reports
• Revenue cycle automation with AI agents and a specialist in the loop
• Speech and call analytics that surface revenue nobody was listening for
• Data products and real-world-evidence platforms for partner and research revenue