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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.
About Mnexium on Product Hunt
“Persistent memory for LLM apps across every model”
Mnexium was submitted on Product Hunt and earned 11 upvotes and 1 comments, placing #36 on the daily leaderboard. 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.
On the analytics side, Mnexium competes within API, Developer Tools and Artificial Intelligence — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Mnexium performed against the three products that launched closest to it on the same day.
Who hunted Mnexium?
Mnexium was hunted by marius ndini. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Mnexium including community comment highlights and product details, visit the product overview.
marius ndini