End side large model

1. Multi-platform support

Deep integration of domestic and foreign head mainstream large model resources, covering multi-type general and vertical model capabilities. Combined with the characteristics of different business scenarios, functional demands and performance indicators, flexible scheduling and intelligent matching on demand, the optimal adaptation model and landing scheme are selected to ensure the efficient and stable landing of all kinds of business.

2. End-side AI model

Self-developed lightweight end-side model, through the joint tuning of the front and rear levels, combined with model-driven knowledge base, end-cloud collaboration, hierarchical desensitization and other technologies, for fixed scenarios and high-frequency task depth optimization, the end-side effect can approach the performance of the cloud large model.

3. Vertical knowledge base

Self-developed native vector database base, available.Focus on the segmentation of vertical scene depth customization optimization, combined with business data and use characteristics to do algorithm, architecture, performance special polishing, for the scene. RAGCore applications such as model memory and intelligent retrieval provide differentiated technology empowerment and underlying support.