Service Robot · Products

Xiaoyi Medical Guidance Robot

Xiaoyi (晓医) represents iFlytek’s flagship medical guidance robot, combining advanced speech recognition with medical knowledge graphs to assist patients navigating complex hospital environments. Deployed across major Chinese hospitals since 2017, the robot provides real-time department navigation, doctor scheduling information, and preliminary symptom assessment through natural language conversation.

Product Overview

Developed through iFlytek’s collaboration with Anhui Provincial Hospital, Xiaoyi addresses a persistent challenge in large Chinese hospitals: helping patients find the right department and doctor among dozens of specialties and hundreds of locations. The robot integrates iFlytek’s speech recognition technology with hospital-specific knowledge bases, enabling conversational interactions that guide patients from entrance to consultation room.

Unlike static kiosk systems, Xiaoyi engages patients through voice dialogue, asking follow-up questions about symptoms to recommend appropriate departments. This interactive approach reduces the common problem of patients registering with wrong specialists, improving both patient experience and hospital resource allocation.

Key Features

Xiaoyi’s iFlytek voice engine—covering 169 departments and 13,000+ symptoms—enables conversational symptom triage that routes patients to the right specialist before they reach the registration desk.

  • Voice-Based Interaction: Natural language conversation in Mandarin Chinese with dialect support, allowing patients to describe symptoms or ask questions verbally
  • Multi-Modal Interface: Combines voice, touch screen, and visual displays showing maps, schedules, and health information
  • Real-Time Scheduling: Access to live doctor availability across all hospital departments
  • Symptom Triage: Preliminary assessment guiding patients to appropriate specialties based on described conditions
  • Location Navigation: Turn-by-turn directions to specific rooms, departments, and hospital facilities

Technical Specifications

Xiaoyi’s medical knowledge base covers 618+ navigable points per hospital installation and handles over 2,000 daily conversations at sites like Beijing 301 Hospital.

ParameterSpecification
Speech RecognitioniFlytek voice engine with medical vocabulary
LanguagesMandarin Chinese, major dialects
Knowledge BaseHospital-specific configuration required
Department CoverageUp to 47+ departments per installation
Location Database618+ navigable points (Anhui Provincial Hospital)
Daily Interaction Capacity2,000+ conversations
DisplayTouch screen with visual navigation

Clinical Applications

Xiaoyi operates in hospital entrance halls and outpatient lobbies, serving multiple patient guidance functions:

Pre-Visit Navigation: Patients entering the hospital can ask Xiaoyi for directions to specific departments, registration counters, pharmacies, or examination rooms. The robot provides verbal instructions accompanied by on-screen maps.

Department Recommendation: When patients describe symptoms (“my throat hurts,” “I need a pregnancy checkup”), Xiaoyi asks clarifying questions and recommends appropriate departments, reducing misdirected registrations.

Schedule Inquiries: Patients can query specific doctor availability, specialty clinic schedules, and department operating hours through conversation rather than searching physical directories.

Health Education: Xiaoyi delivers condition-specific guidance on appointment preparation, examination requirements, and post-visit instructions.

At Beijing 301 Hospital, Xiaoyi handles over 2,000 interactions daily, serving 600-700 patients. This volume demonstrates significant capacity to reduce burden on human information desk staff while improving patient flow efficiency.

Deployment Status

Xiaoyi has been deployed across over 50 hospitals in China since its June 2017 launch at Anhui Provincial Hospital. Key installations include:

  • PLA General Hospital (301 Hospital), Beijing
  • Peking Union Medical College Hospital, Beijing
  • Shanghai Ruijin Hospital
  • Anhui Provincial Hospital (first deployment)

The robot operates as part of iFlytek’s broader smart hospital solutions, often integrated with the company’s Intelligent Medical Assistant clinical decision support system.

Regulatory Status

RegionStatusNotes
China (NMPA)Not applicableService robot category; hospital IT system
Europe (CE)--
United States (FDA)--

As a hospital service robot and information system, Xiaoyi operates under hospital IT infrastructure rather than medical device regulations. The robot does not perform diagnostic functions requiring NMPA Class II/III certification.

Frequently Asked Questions

What can Xiaoyi robot do in hospitals?

Xiaoyi provides four primary services: department navigation with voice-guided directions, doctor schedule inquiries across all specialties, symptom-based department recommendations, and answers to common hospital questions about operating hours, procedures, and locations.

How accurate is Xiaoyi’s department recommendation?

Xiaoyi uses iFlytek’s medical knowledge graph covering 169 departments and 13,000+ symptoms to match patient descriptions with appropriate specialties. The system asks clarifying questions to improve accuracy, though complex cases still require human triage nurse assessment.

Is Xiaoyi available in languages other than Chinese?

Currently, Xiaoyi operates primarily in Mandarin Chinese with support for major Chinese dialects. The underlying iFlytek speech technology supports multiple languages, but hospital deployments are configured for Chinese-speaking patient populations.

Can hospitals customize Xiaoyi’s knowledge base?

Yes. Each Xiaoyi deployment requires hospital-specific configuration including department lists, doctor schedules, floor plans, and location databases. The Anhui Provincial Hospital installation, for example, contains 618 navigable locations and 47 department schedules specific to that facility.

Last modified: January 15, 2026

Sources

Publicly available references used for the data on this page. See data methodology for verification standards.