Mnexium AI is a memory infrastructure layer for AI products, providing persistent, explainable, and automatic memory. It solves the problem of AI agents forgetting context between sessions, enabling them to learn and improve over time by storing user preferences, facts, and task states.
Freemium
How to use Mnexium AI?
Integrate Mnexium by adding an `mnx` object to your existing OpenAI API calls. It automatically logs conversations, learns key information, recalls relevant context for returning users, and manages agent state. This allows you to build chatbots that remember user preferences, agents that can resume interrupted multi-step tasks, and SaaS applications with isolated, per-user memory.
Mnexium AI 's Core Features
Chat History: Maintains a raw log of every message within a session for seamless context continuity, ensuring conversations flow naturally without losing track.
Agent Memory: Extracts and persistently stores facts, preferences, and user context across all conversations and sessions, building a long-term user profile.
Agent State: Manages short-term, task-scoped working memory for agentic workflows, tracking progress and pending actions like emails or payments.
Observability: Provides a full audit trail of every API call, memory creation, and authentication event, offering complete transparency into agent decisions.
Simple Integration: Requires no SDK; just add the `mnx` parameter to your API calls. It handles storage, embeddings, and retrieval automatically.
Automatic Persistence & Recall: With `log:true` and `learn:true`, it automatically stores important details and injects relevant prior context when users return.
Semantic Search: Allows searching memories by semantic similarity, enabling the AI to find relevant past information based on the current query's meaning.
Mnexium AI 's Use Cases
Personalized Chatbots: For developers building customer support bots that remember user names and preferences across sessions, eliminating repetitive questions.
Resumable Agents: For travel or booking platforms needing agents that can track multi-step tasks and resume exactly where a user left off after a break.
Multi-tenant SaaS: For B2B software companies requiring isolated memory per workspace or organization to prevent data cross-contamination between clients.
Tool Output Tracking: For workflow automation where agents need to track pending actions like sent emails or open tickets within their short-term state.
Context-Aware Assistants: For any application where AI needs to maintain conversation history and learned user details to provide coherent, personalized interactions.
Mnexium AI 's Pricing
Beta
Free
Free tier for beta testers and early customers. Includes up to 500 Memory Actions, 10,000 API calls, and all documented features.
Pro & Enterprise
Coming Soon /month
For production applications requiring scale and reliability. Contact for pricing details.
