Mnexium AI
Mnexium is a memory infrastructure platform that provides AI agents with long-term memory capabilities through four complementary systems for context management, enabling continuous learning and improvement over time.
https://mnexium.com/?ref=producthunt
Product Information
Updated:Jan 4, 2026
What is Mnexium AI
Mnexium is an advanced memory layer built specifically for AI agents that solves the problem of context loss between sessions. Unlike traditional chatbots that forget everything when a session ends, Mnexium enables AI agents to maintain persistent memory across conversations through a structured system of storing, recalling and managing contextual information. The platform integrates seamlessly with existing AI applications and handles critical memory functions like scoring, deduplication, governance and chat history management.
Key Features of Mnexium AI
Mnexium is a memory infrastructure platform for AI agents that provides persistent context management across sessions. It offers four complementary systems: chat history logging, agent memory for user preferences/facts, agent state tracking for tasks, and full observability. The platform enables AI agents to learn from conversations, store important information, and automatically recall relevant context, all while maintaining security and providing simple API integration.
Persistent Memory System: Maintains context and user information across multiple sessions, allowing AI agents to remember past interactions and user preferences even after sessions end
Four-Component Memory Architecture: Integrates chat history, agent memory, agent state, and observability systems to provide comprehensive context management
Simple API Integration: Easy integration with existing OpenAI code through a simple mnx object addition, requiring no SDK and using pure REST/JSON
Automated Memory Management: Handles scoring, deduplication, governance, and semantic search automatically without requiring complex vector database setup
Use Cases of Mnexium AI
Personalized Customer Service: Chatbots that remember user preferences and previous interactions to provide more consistent and personalized support
Multi-Step Task Agents: AI agents that can maintain context through complex, multi-step processes without losing progress
Personal Assistant Applications: AI assistants that learn user preferences over time and provide increasingly personalized recommendations
Pros
Simple integration with existing AI applications
Comprehensive security with encryption and granular permissions
No need for separate vector database setup
Cons
Currently limited to OpenAI models primarily
Pricing structure not fully established (still in beta)
Relatively new product with potential limitations in production environments
How to Use Mnexium AI
Sign up for an account: Go to mnexium.com and create a free beta account to get access to up to 500 Memory Actions and 10,000 API calls
Add Mnexium to existing OpenAI code: Add an 'mnx' object to your API calls. Mnexium will proxy to OpenAI and handle memory automatically using REST/JSON - no SDK required
Configure OpenAI API key: Pass your OpenAI API key via the x-openai-key header. The key is only used during requests and is not stored
Start using memory features: The system will automatically begin storing chat history, agent memory (facts/preferences), agent state (task progress), and provide full observability logs
Monitor memory usage: Use the observability features to view the full audit trail of API calls, memory creation, and authentication events to understand how your agent is using memory
Scale usage as needed: Start with free beta tier and upgrade to Pro/Enterprise plans when ready for production scale and reliability
Mnexium AI FAQs
Just add an 'mnx' object to your API calls. Mnexium proxies to OpenAI and handles memory automatically. No SDK is required—it's pure REST/JSON.
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