Agent Memory
Persistent memory layer for AI agents. Store context, conversation history, and preferences across sessions with vector and graph-based retrieval.
3 MEMORIES
MEMORY_V1Knowledge Graph12 nodes · 8 edges
user
context
pref
userPrefers dark mode0.95
factWorks at Acme Corp0.91
prefUses Python primarily0.88
Vector + Graph
ArangoDB<50ms recall
PERSISTENT CONTEXT
Give your agents long-term memory.
Vector search + knowledge graph. Store and recall memories with sub-50ms latency. Automatic summarization and entity extraction.
Vector Storage
Semantic search across all stored memories and context.
Knowledge Graph
Relationship-based memory with entity extraction and linking.
User Profiles
Persistent profiles that evolve with every interaction.
Auto-Summarize
Automatic summarization of long conversation histories.
WHY MEMORY
Build agents that remember.
Persistent, personalized context for every agent.
Sub-50ms Recall
Lightning-fast memory retrieval that won't slow your agents.
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Privacy First
Full data isolation per user with encryption at rest.
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Simple SDK
Store and recall memories with just a few lines of code.
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