Build Persistent Memory
for AI Applications
Get started in minutes, scale to millions
1from powermem import create_memory23# Auto-load from .env4memory = create_memory()56# Add memory7memory.add("User likes coffee", user_id="user123")89# Search memories10memories = memory.search("user preferences", user_id="user123")
Core Features
Complete intelligent memory management solution for AI applications
Developer Friendly
Developer Friendly
Provides a simple Python SDK, automatically loads configuration from .env files, enabling developers to quickly integrate into existing projects
- •Lightweight Integration
Intelligent Memory Management
Intelligent Memory Management
Automatically extracts key facts from conversations through LLM, intelligently detects duplicates, updates conflicting information, and merges related memories. Based on cognitive science, implements time-decay weighting to prioritize recent and relevant memories.
- •Intelligent Memory Extraction
- •Ebbinghaus Forgetting Curve
- •Automatic Duplicate Detection
Multi-Agent Support
Multi-Agent Support
Provides independent memory spaces for each agent, supports cross-agent memory sharing and collaboration, and enables flexible permission management through scope control
- •Agent Shared/Isolated Memory
- •Cross-Agent Collaboration
- •Flexible Permission Management
- •Scope Control
Multimodal Support
Multimodal Support
Automatically converts images and audio to text descriptions for storage, supports retrieval of multimodal mixed content (text + image + audio), enabling AI systems to understand richer contextual information
- •Text, Image, and Audio Memory
Deeply Optimized Data Storage
Deeply Optimized Data Storage
Implements data partition management through sub stores with automatic query routing. Combines multi-channel recall capabilities of vector retrieval, full-text search, and graph retrieval for precise retrieval of complex memory relationships.
- •Sub Stores Support
- •Hybrid Retrieval
- •Multi-Hop Graph Traversal
Why Choose PowerMem?
Accurate, Agile, Affordable - The best AI memory management experience
Real-world performance metrics based on LOCOMO dataset
Accurate
More Accurate
Precise memory retrieval, AI-driven importance scoring, context-aware matching
Agile
Faster
Ultra-fast retrieval response, high-performance async processing, intelligent cache optimization
Affordable
More Economical
Reduce storage costs, intelligent memory management, efficient resource utilization
LLM Score
Get Started in Minutes
Simple installation, start building your AI applications immediately
Install
pip install powermem
Basic Usage
from powermem import create_memory# Auto-load from .envmemory = create_memory()# Add memorymemory.add("User likes coffee", user_id="user123")# Search memoriesmemories = memory.search("user preferences", user_id="user123")
Multi-Agent Scenario
# Create independent memories for different agentssupport_memory = create_memory(agent_id="support_agent")sales_memory = create_memory(agent_id="sales_agent")# Add agent-specific memoriessupport_memory.add("Customer prefers email support", user_id="customer123")