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Mnexium is an AI memory infrastructure designed to provide persistent, explainable, and automatic long-term memory for AI agents and products. It enables AI applications to remember user preferences, maintain conversation context, track multi-step tasks, and learn over time, preventing context loss and repetitive interactions across sessions.

5.0
Added
2026-01-04
Price type:
Freemium
Monthly traffic:
6.5K

Mnexium Overview

Mnexium serves as the crucial memory layer for advanced AI products, offering persistent, explainable, and automatic context management. It addresses the common challenges of AI agents losing context, users repeating themselves, and tasks resetting, by equipping AI with long-term memory capabilities. This infrastructure is built on four complementary systems: Chat History, Agent Memory, Agent State, and Observability, ensuring that AI agents can truly learn and improve over time.

How to use Mnexium

Integrating Mnexium into existing AI applications is straightforward, requiring no SDKs. Developers simply add an mnx object to their OpenAI API calls. Mnexium then automatically handles storage, embeddings, and retrieval of memory. Key parameters within the mnx object like log: true enable logging of conversation turns, history: true prepends prior messages for context, and learn: true allows the AI to intelligently decide what's worth remembering. For task-scoped context, Agent State can be loaded with state: { load: true, key: "current_task" }. API keys for Mnexium and your own OpenAI key are passed via headers for secure and controlled access.

Core Features of Mnexium

  • Chat History: Automatically logs every message within a session to maintain conversation continuity.
  • Agent Memory: Extracts and stores facts, preferences, and context about users, persisting this knowledge across all conversations and sessions.
  • Agent State: Provides short-term, task-scoped working context to track task progress and pending actions for agentic workflows.
  • Observability: Offers a full audit trail of API calls, memory creation, and authentication events, allowing developers to understand agent behavior.
  • Memory Versioning: Automatically handles conflicting memories by skipping duplicates and superseding outdated information, while retaining old versions for audit.
  • Profiles: Provides structured, schema-defined user data (e.g., name, email, timezone) that can be automatically extracted or manually updated.
  • System Prompts: Manages and injects instructions at project, subject, or chat level, allowing for dynamic and layered prompt resolution.
  • Simple Integration: Seamlessly integrates with existing OpenAI API calls via a simple JSON object, without requiring separate SDKs.
  • Data Security: All data is encrypted at rest and in transit, with support for scoped API keys and instant access revocation.

Use Cases for Mnexium

Mnexium is designed for a variety of real-world AI applications where memory and context are critical. It can be used to build personalized chatbots that remember user preferences across sessions, eliminating repetitive questions. For multi-step agentic workflows, it enables resumable agents that track task progress and pick up exactly where they left off, even if a user leaves mid-task. Multi-tenant SaaS applications can leverage Mnexium to map project IDs to organizations and subject IDs to users, ensuring isolated memory for each workspace. Furthermore, it facilitates tool output tracking, allowing agents to monitor pending actions like emails or payments.

Advantages of Mnexium

The primary advantage of Mnexium is its ability to provide AI agents with persistent, intelligent memory, significantly enhancing user experience and agent efficiency. Its automatic context management systems prevent agents from losing information, leading to more natural and effective interactions. The explainability feature, through full observability, allows developers to debug and understand why certain memories were used. Simple, no-SDK integration reduces development overhead, while robust data security and governance features ensure enterprise readiness. Mnexium's predictable pricing model and generous free tier also make it accessible for developers to start building scalable AI applications.

Pricing and Plans

Mnexium offers a generous free tier for developers and predictable pricing for production workloads. The Beta Free plan includes up to 500 Memory Actions and up to 10,000 API calls, with access to all documented features. For Pro & Enterprise plans, which are designed for production apps requiring scale and reliability, pricing information is marked as 'Coming Soon/month' and customers are encouraged to contact Mnexium for more details.

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