Extract Structured Intelligence from Unstructured Clinical Data
Transform clinical notes, discharge summaries, radiology reports, and prior auth letters into governed, FHIR-native structured data — at scale.
The AI Pipeline
Document Ingestion
Clinical notes, discharge summaries, radiology reports, pathology, and prior auth letters are ingested from any EHR, portal, or document store.
De-Identification
HIPAA Safe Harbor and Expert Determination compliance — auto-redact all 18 PHI identifiers before any processing occurs.
Entity & Concept Extraction
AI-powered extraction identifies diagnoses, medications, procedures, vitals, lab values, and symptoms from free text.
Terminology Mapping
Automatically map extracted concepts to ICD-10, CPT, SNOMED CT, LOINC, RxNorm, and NDC without manual coding.
FHIR Structuring
Output as FHIR R4 Observations, Conditions, MedicationRequests, and DiagnosticReports — ready for downstream analytics.
Use Cases
Prior Auth Acceleration
Analyze prior auth documents automatically and surface the clinical evidence needed to accelerate approval decisions.
Clinical Note Coding
Auto-suggest ICD-10 and CPT codes from clinical documentation — reduce coder workload by up to 60%.
Adverse Event Detection
Detect risk signals and adverse events from unstructured notes before they surface in claims or incident reports.
Population Health Gaps
Identify care gaps, chronic condition cohorts, and outreach candidates from clinical text at population scale.
Quality Measure Extraction
Extract HEDIS and Stars measure data from clinical notes — without manual chart review.
Referral Summarization
Automatically summarize referral letters and route them to the appropriate specialist workflow.
