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MedzyAI Document Classifier

seuraavan mukaan: Medzy Inc

MedzyAI Document Classifier is an AI patient document parser for pharmacy and other healthcare uses

Speed up patient document classification and parsing using MedzyAI's Smart Document Classifier!

  • Our solution is a quick and secure way for healthcare professionals to streamline their patient document processing tasks, eliminating paperwork and simplifying operations.
  • Comply with Quebec's safety and security protocols: our solution is hosted in Microsoft's Canada-East datacenter.
  • Keep your data private. Our solution only stores your document's metadata: file size, file type, processing timestamp, number of pages and number of AI tokens (for billing). We do not keep any records of your documents private content.
  • Easily integrate with your system with our developer friendly API documentation: https://documentclassifier.medzy.ai/docs
  • Our latest solution (V3.2.0) can recognize 16 document types and 30 sub-types. Document types that are properly parsed by our solution are underlined. More will come in the next releases.
    1. Prescription (including 8 different templates / sub-types)
    2. Patient pharmacy transfer (list of prescriptions transferred)
    3. Patient pharmacy transfer request
    4. Patient consultation form (Empego, minor ailments, law 31-41)
    5. Prescription renewal/update request
    6. Patient pharmacology profile
    7. Patient pharmacology profile request
    8. Patient consent form
    9. Lab test request
    10. Lab test result
    11. Doctor's note
    12. Insurance (notice, card)
    13. OPQ notice (Ordre des Pharmaciens du Québec)
    14. RAMQ notice (Regime de l'Assurance Maladie du Québec)
    15. Quebec GAP Form (Guichet d'Accès à la Première ligne)
    16. Distributor notices and product information
  • Key features
    1. Base parser: if the document type is unknown or not currently supported by a specialized parser, certain common fields will still be extracted: document_sender, document_receiver, patient information.
    2. Parse document: if you already know the document type, you can skip the classification and use the /parse route to extract content
    3. Documentation now enumerates (dropdown) of the different document types accepted by the /parse route
  • Release notes V3.2.0 (2025-06-25)
    1. Added model benchmarking infrastructure and test suite for prescription and patient transfer documents (benchmarking results to be published soon)
    2. Consumption visibility: Added the /usage route to help you monitor your consumption
    3. Granular billing: new billing dimension classified pages (separated the OCR from the classification), reduced the OCR pricing accordingly
    4. Optimized OCR usage: used a most cost-effective OCR for most documents, reducing reliance on the higher-priced alternative

Yhdellä silmäyksellä

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https://store-images.s-microsoft.com/image/apps.28439.80058a81-2ac4-425c-8bf5-961fc887d304.f2d66fc0-7639-45a8-976a-efb0eaffd4c1.e8dc87b7-c048-43f1-9dac-895972bbe8f9