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AI for Clinical Document Triage & Healthcare Classification
Beag Labs builds custom small language models (500M-5B parameters) for clinical document triage and healthcare classification. Trained on your data, deployed in HIPAA-compliant environments — on-prem, air-gapped, or in your VPC. No PHI sent to external APIs.
What you can automate.
Clinical document triage
Route incoming clinical documents to the right review queue based on content, urgency, and document type.
Adverse event classification
Identify and classify adverse event reports from unstructured clinical narratives for pharmacovigilance teams.
Prior authorization extraction
Extract relevant clinical information from prior authorization requests to accelerate approval decisions.
FDA submission categorization
Categorize and organize FDA submission documents by module, section, and regulatory pathway.
Why teams choose Beag Labs.
- ✓Faster clinical document processing
- ✓Consistent triage decisions
- ✓Reduced administrative overhead
- ✓HIPAA-compliant deployment
Built for your security requirements.
Discuss your healthcare AI use case
Talk to us about your classification, extraction, or relevance workload. We'll show you how a custom SLM deployed in your environment beats a frontier API on cost, speed, and privacy.