Product updates, implementation guides, and notes from the Mnexium team.

Learn how to build memory-aware AI products with durable context, structured data, and production-grade agent infrastructure.

Introducing Integrations: Bring Live External Data Into Mnexium

A deep dive into Mnexium Integrations: why they matter, how pull and webhook modes work, and how teams can inject live operational data into runtime prompts.

Memory Policies: Control What Your AI Remembers

A deeper look at Memory Policies in Mnexium: why they matter, how scoped defaults work, and what teams can accomplish by controlling extraction quality.

Persistent Memory API for AI Apps (OpenAI, Claude, Gemini)

Provider hub page for persistent memory APIs, with direct guides for OpenAI, Claude, and Gemini implementations.

Persistent Memory API for Gemini Apps

Intent guide for Google Gemini teams: add durable memory, context continuity, and history with Mnexium.

Persistent Memory API for Claude Apps

Intent guide for Anthropic Claude teams: add long-term memory and session continuity with Mnexium.

Persistent Memory API for OpenAI Apps

Intent guide for teams building on OpenAI: add durable memory, chat continuity, and structured context without building a custom memory stack.

Introducing Cartly: An iOS Receipt Tracking App Built on Mnexium

Feature-focused breakdown of the Mnexium runtime in Cartly: mnx controls, durable identity, memory flags, records schemas, and deterministic OCR sync.

Introducing the Mnexium n8n Connector

Production-ready Mnexium integration for n8n with chat, memory, profile, records, and custom API operations.

Introducing Memory Policies: Controlled Memory Extraction for AI

Memory Policies let you control extraction behavior with scoped defaults and per-request overrides, so your assistant stores high-signal memories with predictable rules.

Introducing Records: Structured Data for AI Applications

Records give your AI a structured data layer — define schemas, CRUD records via API, query with filters, search semantically, and let the AI create and update records automatically from conversations.

Introducing the Mnexium SDKs for JavaScript and Python

Official SDKs for JavaScript/TypeScript and Python. Add persistent memory, user profiles, structured claims, and conversation history to your AI applications in five lines of code.

Introducing @mnexium/chat: AI Chat for Any Website

A single npm package that adds a polished, production-ready AI chat widget to any website. React, Next.js, Express, or plain HTML — it just works, and most importantly, it remembers.

Memory Decay: How AI Remembers Like Humans Do

Introducing Memory Decay — a system that makes AI memory behave more like human memory. Frequently used memories stay strong, while unused ones naturally fade. The result? More relevant, contextual AI interactions.

Chat Summarization: Cut Your Token Costs by 95%

Long conversations are expensive. Chat Summarization intelligently compresses your conversation history while preserving context, slashing your token costs dramatically with rolling summarization.

Introducing Profiles: Structured User Data for AI

Profiles give your AI applications instant access to key user attributes like names, emails, timezones, and custom fields — all automatically extracted from conversations or set via API.

Hello Mnexium! Getting Started

In this getting started Hello World post - we clone chatGPT using Mnexium. We include memory and conversation history.