AI-powered clinical documentation and medical coding from patient-clinician conversations
Knowtex captures unstructured clinical conversation and generates pre-filled medical notes with coding suggestions—reducing clinician documentation time while improving billing accuracy. The stack reveals a mature ML infrastructure (PyTorch, TensorFlow, SageMaker, Vertex AI, Triton Inference Server) paired with healthcare-grade interoperability (FHIR, HL7) and now integrating Epic Systems, signaling expansion into large health systems. Hiring is accelerating across engineering and support, with active deployment work across VA Medical Centers nationwide, suggesting a shift from startup adoption to government-scale operations.
Knowtex provides an AI documentation platform for clinicians and healthcare organizations. The product records natural conversation between clinician and patient, extracts clinical entities, and auto-generates structured notes with medical coding suggestions for clinician review and sign-off. Core users are physicians and health systems focused on reducing manual note-writing burden and improving claims reimbursement accuracy. The company operates in the US, headquartered in San Francisco, and is currently executing large-scale implementations across federal healthcare facilities.
Frontend: React, React Native, Flutter. Backend: Node.js, Python, PostgreSQL, AWS (ECS, Lambda). ML: PyTorch, TensorFlow, SageMaker, Vertex AI, Triton Inference Server. Healthcare: FHIR, HL7. Currently adopting Epic Systems.
Epic integration, VA Medical Center deployments nationwide, specialty implementation playbooks, clinical decision support console, clinical champion programs, and support infrastructure scaling.
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