Product Launch
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.
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From the blog
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.
Product Update
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.
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Intent Hub
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.
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Intent Guide
Persistent Memory API for Gemini Apps
Intent guide for Google Gemini teams: add durable memory, context continuity, and history with Mnexium.
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Intent Guide
Persistent Memory API for Claude Apps
Intent guide for Anthropic Claude teams: add long-term memory and session continuity with Mnexium.
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Intent Guide
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.
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Case Study
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.
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Product Launch
Introducing the Mnexium n8n Connector
Production-ready Mnexium integration for n8n with chat, memory, profile, records, and custom API operations.
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Product Launch
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.
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Product Launch
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.
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Product Launch
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.
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Product Launch
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.
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Product Update
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.
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Product Update
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.
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Product Update
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.
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Getting Started
Hello Mnexium! Getting Started
In this getting started Hello World post - we clone chatGPT using Mnexium. We include memory and conversation history.
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