Technology Overview
To reduce the workload of physicians and nursing staff, MedBobi 2.0 is an intelligent, multilingual medical assistant platform integrating speech recognition, language understanding, and task-oriented agent technologies. It supports the integration of clinical speech and electronic records to assist in generating and organizing medical notes, nursing documentation, examination summaries, and meeting transcripts.
Through AI-assisted processing, MedBobi 2.0 helps clinicians streamline information flow and reduce administrative and communication burdens. The system adopts a multi-agent architecture capable of supporting various hospital scenarios—such as ward handovers, triage, and patient education—while continuously adapting to institution-specific terminology and workflow.
The technology is applicable to hospitals, clinics, telehealth, and medical data management, helping reduce manpower costs, enhance service efficiency, and enable real-world deployment of intelligent clinical applications.
Technical Superiority
Supports multilingual speech-to-text and semantic understanding to help healthcare professionals efficiently organize clinical documentation and reports, reducing administrative workload and human error.
Utilizes an Agentic AI architecture to enhance adaptability and automation across different clinical scenarios, minimizing customization costs and accelerating deployment.
Provides real-time voice assistance and task-oriented agent collaboration to improve consultation efficiency, strengthen doctor–patient communication, and enhance clinical experience.
Application
Hospitals / Clinics: Assists in clinical speech transcription and medical documentation, improving workflow efficiency and reducing administrative workload.
Telemedicine: Supports multilingual real-time interaction and recording, enhancing accessibility and accuracy in remote healthcare services.
Medical Device Companies: Enables integration of speech recognition and task-agent modules to increase product intelligence and competitiveness.
Academic Research: Facilitates analysis of speech and text data for automated case studies and healthcare trend discovery.
Patients / Families: Provides voice-assisted communication and educational feedback to strengthen doctor–patient interaction and overall care experience.
Multilingual Speech Recognition , Automatic Generation of Doctor-Patient Reports , Multimodal Image Recognition , Enhanced RAG Database