Axiomera turns Epic Clarity extracts, legacy feeds, and acquired-site data into a terminology-bound Domain Intelligence Layer. Deployed as a container in your own cloud, with confidence-scored automation and a human on every clinical decision. Gartner projects 60% of AI projects will be abandoned through 2026 without AI-ready data. Yours doesn't have to be one of them.
Epic Clarity, the acquired hospital's legacy Cerner, an LIS HL7v2 feed, an ambulatory EHR, claims (CPT 83036), inbound HIE C-CDA. Same test, six dialects.
Clarity: varchar "6.9" LIS: local "HGBA1C"
Six shapes become FHIR Observation resources. Whatever they arrived as.
HL7v2 → FHIR C-CDA → FHIR
All six bind to LOINC 4548-4, units normalized to %. The free-text ambulatory value scores 0.71. And routes to your terminologist's queue instead of silently committing.
LOINC 4548-4 · conf 0.96 0.71 → human review
One governed variable in the Domain Intelligence Layer. Lineage back to every source system.
one variable, one truth
Built once, consumed three times:
The data moved. What the fields meant on arrival was left to assumption, and every model built on top inherited the guess. Movement is not meaning.
Ship your first governed, feature-store-grade clinical dataset in weeks. Not the 18 months your last pilot spent on data prep.
Turn Clarity extracts into a terminology-bound layer in the Snowflake, AWS, GCP, or Azure environment you already pay for. Without another one-off pipeline, and with drift detection when a feed changes underneath you.
Make the acquired hospital's legacy Cerner data answer the same questions as your Epic data. Without waiting for the EHR migration to finish.
Quality, registry, and eCQM feeds drawn from one harmonized layer instead of re-mapped per program. Cut the manual abstraction burden.
The federated pattern. 47 U.S. healthcare institutions trained one model with no raw patient record leaving the site that held it, published in Informatics in Medicine Unlocked. Brought to your research enterprise.
Federated learning across 47 U.S. healthcare institutions, published in Informatics in Medicine Unlocked (Elsevier).
Papers published in Elsevier and Frontiers journals, with the harmonization papers under peer review. USPTO Notice of Allowance on App 19/181,522, Evolutionary Neural Networks.
Runs as a native app on Snowpark Container Services; also deploys to AWS, GCP, and Azure. In production today.
An architecture review on your stack, your feeds, and your governance model. Your security team is welcome in the room.