Automem

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AutoMem is an AI Agents & Automation tool that provides AI assistants with durable, relational memory using a graph-vector service. It combines FalkorDB for graph storage and Qdrant for vector embeddings, running on your own hardware.

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At a glance

Pricing

Open Source

Free tier

API

Yes

Skill level

Technical

About

What is automem?

AutoMem is a graph-vector memory service designed to give AI assistants durable, relational memory. Unlike traditional RAG or vector databases, AutoMem stores typed relationships and embeddings, allowing for nuanced recall beyond keyword matching. It scores highly on long-term memory benchmarks like LoCoMo. The service combines FalkorDB for graph storage and Qdrant for vector embeddings, offering a hybrid query system that considers semantic similarity, graph traversal, temporal alignment, tag overlap, and importance. It features neuroscience-inspired memory consolidation cycles, strengthening important memories and allowing less relevant ones to fade. AutoMem is suitable for self-hosting via Docker or Railway and supports integration with various AI clients like Claude, Cursor, and ChatGPT.

Best used for

Ideal for developers, data scientists, and startup founders who need to equip AI assistants with durable, relational long-term memory, understand complex data relationships, and self-host their memory infrastructure. Especially valuable for building AI applications that require nuanced recall and learning beyond simple keyword matching.

Common actions

implement AI memory

manage AI relationships

enhance AI recall

deploy AI memory service

integrate vector database

"AI Agents"github copilotface swappingcollaborationopen-sourceworkflowsautomated workflowdeepfakelow-code/no-code

Capabilities

Key features

Graph-vector hybrid memory
11 authorable relationship types
Memory consolidation cycles
Multi-hop bridge discovery
FalkorDB integration
Qdrant integration
Self-hosting capability

Target Audience

developerdata scientiststartup founder

Integrations

claudechatgptelevenlabsdockerrailway

Pricing & Plans

Open Source

Free

FAQs

What kind of memory does AutoMem provide to AI assistants?

AutoMem offers durable, relational memory by combining graph and vector storage. It stores typed relationships and embeddings, allowing AI assistants to recall not just matching memories but also related decisions, principles, and alternatives, providing a deeper understanding.

How does AutoMem handle memory consolidation and forgetting?

AutoMem implements neuroscience-inspired memory consolidation cycles. It uses daily relevance scoring, weekly processing to discover connections, and monthly clustering to group similar memories. It can also archive or delete low-relevance or very old memories, mimicking natural forgetting.

Can AutoMem be self-hosted, and what are the deployment options?

Yes, AutoMem is designed for self-hosting. It can be deployed using Docker Compose for local development or via Railway for a cloud-based solution. It provides pre-built Docker images for its services, including the API, FalkorDB, and Qdrant.

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Subcategories trending in AI Agents & Automation

Chatbots & Conversational AI General-Purpose Agents Workflow Agents Personal Assistants RAG & Document AI Voice Agents

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