Mnexium - Persistent memory for LLM apps across every model

Mnexium gives AI apps one shared memory layer across models and agents. Add persistent memory, chat history, user profiles, records, and live context with one API. Built for OpenAI, Anthropic, Gemini, and agent workflows, without managing vector DBs, sync jobs, or custom memory pipelines.

Hey Product Hunt! This is my second launch here, and I’m excited to share Mnexium. I built it around a simple problem: LLMs are powerful, but they forget. Most AI apps still have to rebuild memory from scratch: chat history, semantic recall, user profiles, saved records, and the context that should carry across sessions. Mnexium gives developers one API for persistent memory in AI apps. Add an mnx object, connect it to your LLM workflow, and your app can remember users, conversations, preferences, and context over time. I’d love feedback from people building AI assistants, agents, copilots, companions, or any app where memory makes the experience feel more useful and personal.

Mnexium - Persistent memory for LLM apps across every model

Replies