Clinical data platforms
FHIR tooling, validation engines, and data management systems for research teams coordinating clinical data across institutions and studies.
Research software for bioinformatics teams.
We build the infrastructure behind research programs. Data platforms, clinical tooling, validation systems, and LLM integrations for teams working with biological and clinical data.
What we build
Bioinformatics infrastructure
End-to-end systems for managing and analyzing biological data at research scale. Architecture your team can operate.
LLM integrations
Language models applied to genomic and clinical data. Annotation, literature synthesis, structured extraction. Deployed for production research.
Recent work
FHIR resource manager
A pediatric research consortium needed to coordinate clinical data across multiple studies and institutions. Releases were manual, validation was inconsistent, and there was no version history when things went wrong.
We built a platform for uploading, validating, versioning, and releasing FHIR resources to servers. Built-in version control tracks every change with full rollback support. Data freezes create immutable snapshots before major releases. A full API lets bioinformatics teams automate their pipelines.
Studies now deploy to multiple FHIR servers with one-click releases and reviewers always see the same data.
Clinical data validation
A research team was manually comparing clinical records across two systems field by field. Discrepancies in diagnosis codes, date formats, and medication entries delayed every data release.
We built a validation platform that pulls FHIR resources and registry data, runs configurable transform and comparison pipelines per field, and queues mismatches for human review. Fields that match are auto-approved. Reviewers only see what needs attention. Match rate statistics track which fields can be promoted from manual review to automatic over time.
Data releases that required weeks of manual reconciliation now go through a structured review queue.
How it works
01
Domain assessment
Map the research domain. Audit data types, existing tools, and computational infrastructure. Define what needs to be built.
02
Embedded development
Work alongside your researchers. Production code, platform builds, data tooling. Ship working software iteratively.
03
Transfer
Documentation, training, full handoff. Your team owns and operates everything.