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Технологии извлечения данных

  • A Python library providing vector-based shared memory for AI agents to store, retrieve, and share context across workflows.
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    What is Agentic Shared Memory?
    Agentic Shared Memory provides a robust solution for managing contextual data in AI-driven multi-agent environments. Leveraging vector embeddings and efficient data structures, it stores agent observations, decisions, and state transitions, enabling seamless context retrieval and update. Agents can query the shared memory to access past interactions or global knowledge, fostering coherent behavior and collaborative problem-solving. The library supports plug-and-play integration with popular AI frameworks like LangChain or custom agent orchestrators, offering customizable retention strategies, context windowing, and search functions. By abstracting memory management, developers can focus on agent logic while ensuring scalable, consistent memory handling across distributed or centralized deployments. This improves overall system performance, reduces redundant computations, and enhances agent intelligence over time.
  • Innovative AI-driven solutions for healthcare and life sciences.
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    What is linguamatics.com?
    Linguamatics provides cutting-edge natural language processing (NLP) technologies designed specifically for healthcare and life sciences. Leveraging over 6.5 million biomedical synonyms, the platform can extract critical information from diverse documents, making it easier for organizations to harness the full potential of their data. With applications in clinical research, regulatory affairs, and patient care, Linguamatics enables organizations to innovate and scale effectively, ensuring cost-efficient operations and improved patient outcomes.
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