> ## Documentation Index
> Fetch the complete documentation index at: https://docs.memsync.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Introduction
> Build personalized AI experiences with MemSync's portable long-term memory
# Welcome to MemSync
MemSync is a portable memory platform that elevates AI applications from stateless interactions to intelligent, context-aware experiences with persistent long-term memory. It also enables users to seamlessly transfer context and data across different applications into your app.
## Why MemSync?
Traditional AI applications don't have cross-session context.
**MemSync** provides state-of-the-art memory infrastructure that can:
* **Extract meaningful facts** from conversations automatically
* **Store long-term memories** in organized, searchable formats
* **Provide semantic search** to find relevant context instantly
* **Build user profiles** that evolve over time
* **Import external cross-application** context from other AI chat and social media apps
## Quick Start
Get started with MemSync in minutes:
Set up MemSync and make your first API call in under 5 minutes
Explore the complete API documentation with examples
## Core Features
Learn about semantic and episodic memories, how they're extracted and stored
Organize memories into categories like work, hobbies, relationships, and more
Find relevant memories using natural language queries with vector search
Auto-generate user bios and profiles from accumulated memories
## Integrations
Connect MemSync with your existing tools and data sources:
Import context from LinkedIn, Twitter, and Reddit
Process PDFs, Word docs, and other files
Import conversations from ChatGPT and other platforms
## Example Use Cases
### Personalized Chatbots
* Remember customer preferences and past issues
* Provide contextual support based on interaction history
* Track customer journey and satisfaction
### Customer Support
* Remember customer preferences and past issues
* Provide contextual support based on interaction history
* Track customer journey and satisfaction
### Educational Platforms
* Track learning progress and preferences
* Personalize curriculum based on user goals
* Remember areas of difficulty and success
## Getting Started
Ready to build your first personalized AI with memory retrieval?
```python theme={null}
# Get relevant memories for context
memories = memsync.search_memories(
query="What's the latest news related to my educational interests?",
user_id="user123",
limit=5
)
# Use memories to personalize response
context = "\n".join([m.memory for m in memories])
response = llm.generate(context=context, message=user_message)
```
Follow our quickstart guide to set up MemSync and make your first API call