Unstructured Content
PDFs, pathology reports, and clinical notes aren’t analysis-ready
Disparate Systems
Genomic, clinical, and outcomes data live in separate systems
Scalability
Lack of standardized ontologies prevents scalable analysis
Your institution sits on a goldmine of oncology data—but it’s trapped in unstructured documents, siloed systems, and inconsistent formats. You need enterprise-grade data enablement to power registries, analytics, and AI/ML initiatives.
PDFs, pathology reports, and clinical notes aren’t analysis-ready
Genomic, clinical, and outcomes data live in separate systems
Lack of standardized ontologies prevents scalable analysis
AI/NLP-powered extraction from unstructured and semi-structured documents
Ontology-linked, interoperable datasets ready for immediate use
Expert-in-the-loop validation ensures enterprise-grade data quality
Process thousands of documents with metrics and monitoring dashboards
Extract and integrate data from pathology reports, clinical notes, genomic files, and legacy documents.
Real-time dashboards monitor extraction accuracy, completeness, and throughput with expert validation workflows.
Automatically map extracted entities to ICD-O, HGNC, MONDO, HPO, and LOINC terminologies.
HIPAA-compliant cloud or on-premise deployment that scales from pilots to institution-wide implementations.
Bidirectional automation from order to results. Automatically accepting orders from your EHR and delivering discrete genomic findings.
Flexible data models accommodate institutional vocabularies, custom fields, and evolving analytical requirements.
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