> ## Documentation Index
> Fetch the complete documentation index at: https://docs.remem.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Remem

> Universal Context Layer for AI Agents

# Welcome to Remem

Remem is a **universal context layer** that gives your AI agents persistent memory. Ingest personal and professional data, and Remem handles encryption, classification, and retrieval — so your agents always have the right context.

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/quickstart">
    Create a tenant, ingest a document, and query it in 5 minutes.
  </Card>

  <Card title="Authentication" icon="key" href="/authentication">
    API keys, namespace grants, and security model.
  </Card>

  <Card title="Namespaces" icon="folder" href="/namespaces">
    Organize one workspace into isolated memory areas for agents and teams.
  </Card>

  <Card title="Core Concepts" icon="book" href="/concepts">
    Workspace hierarchy, encryption, query modes, and the processing pipeline.
  </Card>

  <Card title="MCP Integration" icon="plug" href="/mcp-integration">
    Connect Remem MCP tools to Claude, Codex, and other MCP clients.
  </Card>

  <Card title="CLI" icon="terminal" href="/cli">
    Query and inspect Remem from terminal scripts and automation.
  </Card>

  <Card title="Agent Toolkit" icon="cpu" href="/agent-toolkit">
    Install `remem-dev-sessions` for Claude and Codex session memory.
  </Card>
</CardGroup>

## Why Remem?

| Feature                                    | Description                                                              |
| ------------------------------------------ | ------------------------------------------------------------------------ |
| **Hard tenant isolation**                  | Per-tenant encryption keys, dedicated vector collections, PostgreSQL RLS |
| **Namespace isolation inside a workspace** | Per-key read/write grants and default namespace routing                  |
| **AI-powered classification**              | Automatic categorization, entity extraction, and sensitivity labeling    |
| **Two query modes**                        | Fast (`<100ms`, hybrid search) and Rich (`<2s`, with LLM synthesis)      |
| **GDPR/CCPA ready**                        | Built-in data export and crypto-shredding deletion                       |
| **MCP native**                             | First-class Model Context Protocol support for agent integrations        |

## Architecture at a Glance

```
Client → FastAPI → Redis Streams → Worker Pipeline
                                      ├── Encrypt & Store (S3 + PostgreSQL)
                                      ├── Chunk & Embed (voyage-3.5-lite)
                                      ├── Classify & Extract (Grok 4 Fast)
                                      └── Index (Qdrant)
```