Memori - Agent-native memory infrastructure

Introduction

Memori is a memory infrastructure built specifically for AI-native applications, designed to give intelligent agents persistent, structured, and retrievable long-term memory. In traditional AI conversations and applications, models often lack effective memory of past interactions, resulting in fragmented user experiences and poor task continuity. Memori solves this by creating a unified memory layer that enables AI agents to "remember" the past, understand context, and continuously learn and grow across multiple interactions. Whether it's a personal assistant, customer service bot, or complex workflow automation system, Memori injects a true "memory soul" into every AI agent.

Key Features

• Long-term memory storage: Persistently saves conversation history, user preferences, key decision points, and more, eliminating the constraints of context window limits.
• Intelligent retrieval and recall: Uses semantic similarity and time-decay algorithms to quickly locate the most relevant pieces of information from vast memory stores.
• Structured memory management: Supports categorization, tagging, priority ranking, and automatic archiving of memories for efficient knowledge organization.
• Multi-agent memory sharing: Allows different agent instances to access the same memory pool, enabling information synchronization and consistency in collaborative scenarios.
• Real-time updates and forgetting mechanisms: Supports dynamic writing of new memories and includes built-in automatic forgetting policies that comply with privacy regulations to ensure data compliance.

Highlights

• Agent-native design: Built from the ground up for AI agents, with seamless integration into mainstream frameworks such as LangChain and AutoGPT — ready to use out of the box.
• High performance with low latency: Employs in-memory indexing and vectorized storage engines, delivering retrieval response times typically in the millisecond range without impacting real-time agent interactions.
• Elastic scalability: Scales smoothly from single-machine development environments to distributed production clusters, accommodating applications of all sizes.
• Privacy and security first: Provides fine-grained access control, data encryption, and user-level memory isolation to meet enterprise-grade compliance requirements.
• Open ecosystem: Offers RESTful APIs and SDKs in multiple languages, giving developers full freedom to customize memory read/write logic and lifecycle management.

Who It's For

Memori is designed for AI application developers who need to add persistent memory capabilities to chatbots, virtual assistants, and similar products to boost user engagement. It also serves automation workflow engineers building multi-step, cross-session agents that must never lose task state, as well as enterprise AI platform teams looking to establish a unified memory service layer supporting multiple internal AI applications. Additionally, researchers and experimenters exploring how memory mechanisms affect agent behavior and long-term learning outcomes will find Memori an invaluable tool for their investigations.