Transform unstructured enterprise documents, medical charts, and operational data into actionable intelligence. We deploy sovereign LLMs, Retrieval-Augmented Generation (RAG), and computer vision pipelines within secure enterprise boundaries.
Tailored machine learning architectures engineered for high accuracy, verifiable audit trails, and strict data governance.
Custom bio-medical named entity recognition (NER) extracting conditions, medications, dosages, and surgical procedures from unstructured notes into FHIR resources.
Self-hosted open weights models (Llama 3, Mistral) paired with private vector databases (Pinecone, Qdrant, pgvector) ensuring zero company data leaves your cloud.
Computer vision OCR parsing complex multi-page financial statements, medical intake forms, insurance claims, and bills of lading with 99%+ field extraction accuracy.
Machine learning classifiers forecasting claim adjudication outcomes before clearinghouse transmission, flagging missing modifiers, or authorization oversights.
Autonomous software agents automating repetitive cross-system data transfer between legacy desktop apps, clearinghouses, and cloud portals.
Automated PHI redaction, hallucination guardrails, differential privacy masking, and comprehensive audit logs satisfying regulatory scrutiny.
See how our biomedical AI model converts unstructured physician notes into structured billing codes in real-time.
Test the clinical note on the right or edit the text. Our extraction engine parses diagnoses, severity, and procedure candidates with confidence scores.
Speak with our AI Research and Engineering team about developing custom NLP parsers, private vector search, or autonomous agents.
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