Turn Clinical Text Into Clinical Intelligence.Into Clinical Intelligence.
Zabrizon builds production-grade clinical AI and NLP systems that extract meaning from unstructured clinical text — automating medical coding, accelerating chart review, enabling ambient documentation, and powering AI-assisted prior authorisation at scale.
Clinical AI & NLP Services
Specialised AI for the unique language, structure, and compliance requirements of clinical data.
Automated Medical Coding
AI-driven ICD-10-CM/PCS and CPT code suggestion and validation — reducing coder workload, accelerating claim submission, and improving first-pass acceptance rates.
- ICD-10-CM/PCS and CPT code suggestion from clinical notes
- HCC capture and risk adjustment coding for value-based care
- Coder workflow integration — Epic, 3M, nThrive, Optum360
- Coding audit and compliance review automation
Ambient Clinical Documentation
Real-time AI transcription and structured note generation from physician-patient conversations — reducing documentation burden and improving data quality in the EHR.
- Ambient AI transcription integrated with Epic and Cerner workflows
- Specialty-specific SOAP note and progress note generation
- Problem list, medication, and allergy extraction and reconciliation
- Quality and hallucination review pipeline for clinical safety
Unstructured EHR Data Extraction
Clinical NLP pipelines that extract structured clinical facts — diagnoses, medications, procedures, vitals, and social history — from free-text notes, discharge summaries, and pathology reports.
- Named entity recognition for clinical concepts (SNOMED, RxNorm, LOINC)
- Relation extraction for diagnosis-medication, temporal, and severity relationships
- De-identification and PHI redaction for downstream AI use
- Integration with FHIR data lakes and clinical data warehouses
AI-Assisted Prior Authorisation Review
Clinical NLP that reads prior auth submissions, extracts clinical criteria, and surfaces evidence for or against medical necessity — reducing clinician review time by up to 80%.
- Clinical criteria extraction from PA request attachments
- Medical necessity evidence mapping to payer clinical guidelines
- Automated determination draft generation for clinical review
- Integration with prior auth workflow systems (Cohere, Availity, payer portals)
Clinical AI Delivery Process
Rigorous clinical validation at every stage — because clinical AI needs to be right, not just fast.
Clinical Use Case & Data Assessment
Define the clinical task, annotation schema, evaluation criteria, and assess available training data quality and volume.
Model Selection & Fine-Tuning
Select and fine-tune the appropriate clinical language model — BioBERT, MedPaLM, GPT-4, or custom — on your de-identified clinical corpus.
Clinical Validation & IRB Coordination
Blind clinical validation by domain clinicians, bias assessment across demographic groups, and IRB coordination where required.
EHR Integration & Workflow Design
Embed the model into clinician workflows via EHR CDS hooks, SMART on FHIR apps, or API integration — designed to minimise alert fatigue.
Production Monitoring & Drift Management
Ongoing accuracy monitoring, data drift detection, retraining pipelines, and clinical review protocols for edge cases and model updates.
Ready to Put Clinical AI to Work?
Tell us about your clinical NLP or AI use case — coding, documentation, chart review, or prior auth — and we'll scope a pilot in 48 hours.