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Aliyun BaiLian Introduces Memory Library with Cross-Session Retrieval and 50% Performance Boost

On April 9, the Alibaba Cloud BaiLian platform introduced the Memory Library feature, built to prevent AI agents from forgetting details in multi-turn conversations and give them long-term memory that persists across sessions. The feature is currently available for free to a limited number of users. Developers can access it directly via API or deploy it with a single click in products like OpenClaw.
The Memory Library system includes four core modules: "extraction, storage, retrieval, and injection." After a conversation ends, the system automatically extracts key information based on predefined rules and saves it. When a user gives a new instruction, the system uses semantic retrieval to accurately find relevant memories and injects them into the context in real time, enabling highly personalized responses. To lower the development barrier, the feature supports white-box configuration, allowing developers to customize memory rules based on user personality, consumption habits, and specific family relationships. In addition, the memory library includes general rules covering mainstream scenarios such as consumer electronics, customer service, sales, and emotional companionship, which can reduce configuration costs by 50%.
In terms of performance, Alibaba Cloud has specifically optimized the search algorithm. Data shows that the average response time for memory search has dropped by 50%, date relevance has increased by 66%, and memory content relevance has improved by 39%. This upgrade marks the evolution of AI agents from simple "single-task processors" to "digital assistants" with continuous cognitive capabilities. In the current industry landscape, where competition among large models is shifting from parameter scale to application deployment, adding long-term memory will significantly enhance the interaction depth and service continuity for agents in complex scenarios.
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On April 9, the Alibaba Cloud BaiLian platform introduced the Memory Library feature, built to prevent AI agents from forgetting details in multi-turn conversations and give them long-term memory that persists across sessions. The feature is currently available for free to a limited number of users. Developers can access it directly via API or deploy it with a single click in products like OpenClaw.
The Memory Library system includes four core modules: "extraction, storage, retrieval, and injection." After a conversation ends, the system automatically extracts key information based on predefined rules and saves it. When a user gives a new instruction, the system uses semantic retrieval to accurately find relevant memories and injects them into the context in real time, enabling highly personalized responses. To lower the development barrier, the feature supports white-box configuration, allowing developers to customize memory rules based on user personality, consumption habits, and specific family relationships. In addition, the memory library includes general rules covering mainstream scenarios such as consumer electronics, customer service, sales, and emotional companionship, which can reduce configuration costs by 50%.
In terms of performance, Alibaba Cloud has specifically optimized the search algorithm. Data shows that the average response time for memory search has dropped by 50%, date relevance has increased by 66%, and memory content relevance has improved by 39%. This upgrade marks the evolution of AI agents from simple "single-task processors" to "digital assistants" with continuous cognitive capabilities. In the current industry landscape, where competition among large models is shifting from parameter scale to application deployment, adding long-term memory will significantly enhance the interaction depth and service continuity for agents in complex scenarios.
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