Imagine a world where AI agents can retain their memories and decisions, enabling them to learn and adapt more effectively. Welcome to Pluribus, a pioneering memory service designed specifically for AI agents, providing a robust solution for storing and retrieving structured memory.

One of the primary challenges faced by AI agents is the loss of constraints and decisions between runs. Traditional prompts and RAG systems do not preserve this critical information, requiring agents to re-derive it each time. Pluribus addresses this issue by offering a global, shared memory that allows agents to resume work with prior context, ensuring decisions persist across sessions.

The key features of Pluribus include:

• Global, shared memory across agents, enabling seamless collaboration and knowledge sharing
• Persistent decisions across sessions, allowing agents to build upon previous experiences
• Multiple agents operating on the same memory, facilitating complex problem-solving and distributed learning
• Constraints can be enforced instead of ignored, ensuring that agents operate within established boundaries

With Pluribus, agents can recall compiled information using tags and a retrieval query, and proposed changes can be evaluated against existing memory. This groundbreaking service is available on GitHub and can be run locally or on a LAN, making it an ideal solution for AI developers and researchers seeking to unlock the full potential of their AI agents.

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