Multimodal Memory for AI Agents

Seamlessly Store and Recall Text, Images, Audio, and Video

MemU allows your AI to manage diverse types of data within a unified memory framework. All raw information is preprocessed, preserved without loss, and converted into textual memory items for consistent extraction, organization, and retrieval.

Experience Multimodal Memory

Core Multimodal Memory Features

Cross-Modality Storage

Store text, images, audio, and video in the resource layer without compression, maintaining original fidelity for downstream processing.

Unified Text Representation

All multimodal data is extracted and converted into textual memory items, allowing AI agents to operate consistently across modalities.

Flexible Retrieval

MemU enables semantic access to information regardless of its original modality, supporting advanced reasoning and context-aware operations.

Preserved Context

By maintaining all original data and mapping it to memory items, the AI preserves full context for each interaction or knowledge unit.

The Mechanics Behind Multimodal Memory

Step 1: Data Ingestion

Raw data from multiple modalities (text, images, audio, video) is cleaned and preprocessed according to modality-specific rules before storage in the resource layer.

Step 2: Memory Extraction

The MemU agent extracts key information from raw data and converts it into textual memory items, serving as a unified abstraction layer for AI memory operations.

Step 3: Organization and Linking

Memory items are organized and linked across categories or subgraphs to ensure context is preserved and relationships between different modalities are maintained.

Step 4: Semantic Retrieval

Text-based memory items allow the AI to perform retrieval and reasoning seamlessly, regardless of the original data type, supporting both single- and multi-hop queries.

How AI Agents Use Multimodal Memory

Multimedia Recall

AI can store videos and images alongside textual notes, linking them to contextual events or conversations. This enables agents to recall visual and auditory memories together with text-based interactions.

Event Documentation

Record meetings, presentations, or live sessions in multiple formats, then unify and link them as memory items for quick retrieval and contextual understanding.

Creative Project Management

Track sketches, audio drafts, and textual notes together, automatically associating them with the project timeline or previous iterations to support cohesive content creation.

Why Your AI Agent Needs Multimodal Memory

Richer, More Natural Interaction

Move beyond text-only memory. When your AI remembers visuals, voices, and written context together, its responses feel more human, intuitive, and situationally aware.

Remember Anything, Not Just Words

Whether it's an image you uploaded, a video walkthrough, a voice memo, or a typed message—your AI retains all of it as part of one coherent memory system.

Human-Like Multimodal Reasoning

Just like the human brain connects a scene, a sound, and a sentence into one memory, MemU allows AI to form cross-modal associations and retrieve them semantically.

Deeper Understanding Across Sessions

Multimodal recall enables the agent to maintain long-term awareness of events, workflows, preferences, and contexts that span text and media.

Ready to Unlock the Full Potential of AI Memory?

Memory Storage

Store complete historical data from your AI system, preserving full context across conversations, logs, and multi-modal inputs for reliable retrieval and analysis.

Explore Memory Storage

Memory Item

Manage and store individual memory entries for your AI, making each piece of data instantly accessible.

Explore Memory Item

Memory Category

Organize memories into categories for better retrieval, context management, and structured learning.

Explore Memory Category

Memory Retrieval

Access relevant memories instantly using LLM-based semantic reading or RAG-based vector search.

Explore Memory Retrieval

Memory Graph

Transform isolated memory items into an interconnected knowledge network.

Explore Memory Graph

Self‑evolving

AI memories automatically adapt and evolve over time, improving performance without manual intervention.

Explore Self‑evolving

Multimodal Memory

Store and recall text, images, audio, and video seamlessly within a single AI memory system.

Now Here

Multi‑agent

Enable multiple AI agents to share and coordinate memories, enhancing collaboration and collective intelligence.

Explore Multi‑agent

Agentic Memory

With memU's agentic architecture, you can build AI applications that truly remember their users through autonomous memory management.

Explore Agentic Memory

File Based Memory

Treat memory like files — readable, structured, and persistently useful.

Explore File Based Memory

How to Save Your AI Agent’s Memories with memU

Cloud Platform

Use the memU cloud platform to quickly store and manage AI memories without any setup, giving you immediate access to the full range of features.

Try the Cloud Platform

GitHub (Self-hosted Open Source)

Download the open-source version and deploy it yourself, giving you full control over your AI memory storage on local or private servers.

Get it on GitHub

If you want a hassle-free experience or need advanced memory features, reach out to our team for custom support and services.

FAQ

Agent memory (also known as agentic memory) is an advanced AI memory system where autonomous agents intelligently manage, organize, and evolve memory structures. It enables AI applications to autonomously store, retrieve, and manage information with higher accuracy and faster retrieval than traditional memory systems.

MemU improves AI memory performance through three key capabilities: higher accuracy via intelligent memory organization, faster retrieval through optimized indexing and caching, and lower cost by reducing redundant storage and API calls.

Agentic memory offers autonomous memory management, automatic organization and linking of related information, continuous evolution and optimization, contextual retrieval, and reduced human intervention compared to traditional static memory systems.

Yes, MemU is an open-source agent memory framework. You can self-host it, contribute to the project, and integrate it into your LLM applications. We also offer a cloud version for easier deployment.

Agent memory can be used in various LLM applications including AI assistants, chatbots, conversational AI, AI companions, customer support bots, AI tutors, and any application that requires contextual memory and personalization.

While vector databases provide semantic search capabilities, agent memory goes beyond by autonomously managing memory lifecycle, organizing information into interconnected knowledge graphs, and evolving memory structures over time based on usage patterns and relevance.

Yes, MemU integrates seamlessly with popular LLM frameworks including LangChain, LangGraph, CrewAI, OpenAI, Anthropic, and more. Our SDK provides simple APIs for memory operations across different platforms.

MemU offers autonomous memory organization, intelligent memory linking, continuous memory evolution, contextual retrieval, multi-modal memory support, real-time synchronization, and extensive integration options with LLM frameworks.

Start Building Smarter AI Agents Today

Give your AI the power to remember everything that matters and unlock its full potential with memU. Don’t wait — start creating smarter, more capable AI agents now.

Quick Start