Mnexium AI - Memory Infrastructure for AI Agents

Mnexium provides a memory infrastructure designed for AI agents, enabling persistent, explainable, and automatic memory management. This innovative solution addresses common issues faced by AI products, such as losing context and requiring users to repeat themselves. With Mnexium, AI agents can learn and improve over time, offering a more seamless user experience.

1. Persistent Memory

   Mnexium allows AI agents to retain memory across sessions, ensuring that users do not have to repeat themselves. This feature enhances context continuity and improves user interactions.

2. Context Management Systems

   The platform includes four complementary systems: Chat History, Agent Memory, Agent State, and Observability, which work together to manage context effectively.

3. Simple Integration

   Mnexium can be integrated easily into existing applications without the need for SDKs. Developers can add the mnx object to their OpenAI API calls for automatic memory handling.

4. Automatic Persistence

   By setting specific parameters, Mnexium logs every interaction automatically, allowing the AI to learn from conversations and recall relevant context later.

5. Smart Memorization

   The AI determines what is worth remembering, optimizing memory usage and enhancing the relevance of recalled information.

6. Security and Control

   Users maintain control over their data, with all information encrypted and securely managed. Mnexium ensures that users can revoke access and manage permissions effectively.

1. Sign up for a free account on the Mnexium website to get started.
2. Familiarize yourself with the API documentation to understand how to implement the mnx object in your existing code.
3. Experiment with different memory settings to see how they affect your AI's performance.
4. Utilize the observability features to track memory usage and understand how your AI is learning over time.
5. Test the integration with various OpenAI models to find the best fit for your application.

What is Mnexium?

Mnexium is a memory infrastructure designed for AI agents, providing persistent memory management that enhances user interactions by retaining context across sessions.

How does Mnexium work?

Mnexium integrates with existing AI applications to provide a memory layer that automatically logs interactions, learns from user preferences, and recalls relevant context when needed.

Can I use my own OpenAI API key with Mnexium?

Yes, users can pass their OpenAI API key via the x-openai-key header during requests, ensuring that their key is not stored by Mnexium.

How is Mnexium different from a vector database?

Mnexium is specifically designed as a memory layer for AI agents, focusing on scoring, deduplication, governance, and chat history, rather than just handling embeddings.

Pricing information is currently not available on the website. Users are encouraged to check the official site for updates regarding pricing tiers and options.

1. Mnexium effectively addresses the common challenges faced by AI agents, such as context loss and user repetition, making it a valuable tool for developers.
2. The integration process is straightforward, allowing for quick implementation in existing applications.
3. However, the platform is still in beta, which may lead to potential bugs or limitations in functionality.
4. Users may require additional support and documentation to fully leverage the advanced features, particularly in understanding memory management and optimization.
5. Overall, Mnexium shows promise in enhancing AI interactions, but ongoing development and user feedback will be crucial for its success.