• Knowledge generation and retrieval with real-time, high-accuracy multimodal knowledge retrieval for agents This technology uses knowledge bases to continuously detect source data changes and convert raw data into knowledge in near real-time. It converts multimodal data into high-accuracy knowledge through multimodal lossless parsing and token-level encoding, with a retrieval accuracy of over 95%.
  • KV cache for inference acceleration, using historical memory data to improve the inference efficiency of agents The intelligent tiering and management of the KV cache greatly reduce repeated computing during inference for lower inference latency, improve inference throughput and user experience, and deliver strong performance support for long-sequence and complex agent inference

  • .Memory extraction and recall with personalized and continually summarized memory for agents This technology uses memory banks to accumulate working memory and experiential memory during AI agent interaction. It supports memory backtracking and multi-agent collaborative learning to continuously optimize inference accuracy and efficiency, making models smarter with use.