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LAN-YOU INTELLIGENT DIAGNOSIS PRODUCT


About Product
The Lan-you Intelligent Diagnosis Product utilizes AI technology to generate diagnostic knowledge graphs. It automatically generates guided repair procedures and fault analysis reports centered around failure modes, helping automotive enterprises build a comprehensive diagnostic knowledge mid-platform. This enables intelligent and digital assistance throughout the entire diagnosis and repair process, improving efficiency and accuracy.
Features
  • 01
    AI-Powered Truly Intelligent Diagnosis
    Integrates AI technology and intelligent diagnosis, enabling automatic generation of diagnostic strategies through intelligent identification and extraction of repair manual and repair cases.
  • 02
    Knowledge Graph Reconstructing Repair Manuals
    Models and analyzes faults using knowledge graphs, describing typical fault characteristics through quantifiable/measurable data.
  • 03
    More Dimensional and Comprehensive Early Fault Warning
    Establishes exclusive analysis schemes for different faults, and utilizes various signal types such as CAN, RTM, and DTC as early warning data sources of faults.
  • 04
    More Accurate and Efficient Fault Diagnosis
    Based on the data analysis strategies associated with fault modeling, supplemented by self-learning strategies accumulated from big data, to achieve automatic system recommendation of the optimal diagnosis solution.
Scenarios
Applicable to various user roles including OEM R&D engineers, after-sales experts, repair technicians, online customer service, and vehicle owners, supporting topic analysis and data maintenance through system process tools. Diagnostic experience from experts is accumulated and stored via the knowledge mid-platform to assist repair technicians in rapid learning and growth. The diagnostic process is guided by system-led operations. After early vehicle warning, online service agents proactively contact vehicle owners to provide services, and vehicle owners can also consult electronic manuals for self-troubleshooting.

Applied Scenarios
Values
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