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Build Agents that Learn,
With Memory that Lasts.

Meet MemMachine, an open-source memory layer for advanced AI agents. It enables AI-powered applications to learn, store, and recall data and preferences from past sessions to enrich future interactions. MemMachine's memory layer persists across multiple sessions, agents, and large language models, building a sophisticated, evolving user profile. It transforms AI chatbots into personalized, context-aware AI assistants designed to understand and respond with better precision and depth.

Agents without Memory Forget

See how an agent with memory provides a compassionate, personalized healthcare experience, while one without creates frustration.

Without MemMachine

Patient 10:14 AM

Hi, I need to schedule my 3-month follow-up with Dr. Anya Sharma.

Healthcare AI 10:14 AM

Of course. Dr. Sharma has an opening next Tuesday at 9:00 AM. Does that work for you?

Patient 10:15 AM

No. I need an afternoon appointment. What do I need to do to prepare?

Healthcare AI 10:15 AM

You will need to fast for 12 hours before your appointment for the blood test.

With MemMachine

Patient 10:14 AM

Hi, I need to schedule my 3-month follow-up with Dr. Anya Sharma.

MemMachine AI 10:14 AM

Of course, Jane. Dr. Sharma has a 9:00 AM slot on Tuesday, but I remember you dislike morning appointments and find fasting difficult. Would you prefer an afternoon slot on Wednesday at 2:00 PM instead? That one doesn't require fasting.

Memory is the Key to Personalization

A generic agent follows a script, ignoring a patient's personal needs and creating a sterile, one-size-fits-all experience. An agent powered by MemMachine remembers what makes each patient unique, allowing it to provide truly empathetic and personalized care.

Go beyond Question and Answer

Build Context-Aware Agents

MemMachine allows your agents to retain and recall information across multiple sessions. They'll understand the full context of a conversation, leading to more relevant, intelligent, and human-like interactions.

Deliver True Personalization

Our Personalization Memory lets agents remember key facts about their users. By recalling preferences, history, and important details, your agent can provide tailored responses that build trust and long-term engagement.

Unlock Complex Workflows

An agent with memory can manage complex, long-running tasks that require remembering previous steps, user feedback, and evolving goals. From managing a CRM to assisting in a healthcare journey, memory is the key to sophisticated automation.

The MemMachine Architecture

MemMachine Architecture Diagram

Agents Interact via the API Layer

Users interact with an agent, which connects to the MemMachine Memory core through a RESTful API, Python SDK, or MCP Server.

MemMachine Manages Memory

MemMachine processes interactions and stores them in two distinct types: Episodic Memory for conversational context and Profile Memory for long-term user facts.

Data is Persisted to Databases

Memory is persisted to a database layer where Episodic Memory is stored in a graph database and Profile Memory is stored in an SQL database.

Build Intelligent Solutions with Agent Memory

Build Smart Agents for Any Use Case

MemMachine's versatile memory architecture can be applied across any domain, transforming generic bots into specialized, expert assistants. Our growing list of examples showcases the endless possibilities of memory-powered agents that integrate into your own applications and solutions.

Explore Our Examples
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Your CRM Assistant

Your agent can recall a client's entire history and deal stage, proactively helping your sales team build relationships and close deals faster.

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A Healthcare Navigator

Offer continuous patient support with an agent that remembers medical history and tracks treatment progress to provide a seamless healthcare journey.

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A Personal Finance Advisor

Your agent will remember a user's portfolio and risk tolerance, delivering personalized financial insights based on their complete history.

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A Content Writer

Build an assistant that remembers your unique style guide and terminology, ensuring perfect consistency across all documentation.

Frequently Asked Questions

MemMachine is an open-source, multi-layered memory system for AI agents. It allows you to equip your agents with Short-Term, Long-Term, and Personalization memory. While many AI models offer some form of built-in memory, MemMachine’s system is model-agnostic, meaning it can support multiple AI models simultaneously, including specialized models hosted in a private cloud or on-premises data center. This capability enables organizations to maintain full control of their data and work with various models without vendor lock-in.

MemMachine is primarily designed for Agent developers and organizations building AI applications. It provides a flexible and scalable memory system that can be integrated into various AI models, allowing developers to enhance their applications with advanced memory capabilities.

Because a frontier lab’s memory service keeps the memory, and its memory service does not work with other models. Many organizations work with multiple models, including specialized models deployed in its private environment, including its VPC in the cloud and its own on-prem data center. They desire a memory system that can support all of these models.

MemMachine is designed with security in mind. The open-source version can be deployed in your private cloud or on-premises environment, giving you full control over your data.

The project was initially incubated by MemVerge to its current state. The project is now community-driven, and we welcome contributors of all backgrounds. MemVerge will continue to assign its engineering team to improve the memory system and support community efforts.

You can get started by visiting our documentation

The source code for MemMachine is available on GitHub

We welcome contributions from the community! You can contribute by reporting issues, suggesting features, or submitting pull requests on our GitHub repository.

You can get support through our community channels by joining our Discord server or filing an issue on our GitHub repository.

An Enterprise version of MemMachine with additional features and dedicated support will be available soon.

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