[docs] OSS Features , Overview , Brushup (#3676)

docs/open-source/features/overview.mdx

@@ -1,56 +1,69 @@
 ---
-title: Overview
-description: 'Build powerful AI applications with self-improving memory using Mem0 open-source'
+title: "Overview"
+description: "Self-hosting features that extend Mem0 beyond basic memory storage"
+icon: "list"
 ---
 
-## Welcome to Mem0 Open Source
+# Self-Hosting Features Overview
 
-Mem0 is a self-improving memory layer for LLM applications that enables personalized AI experiences while saving costs and delighting users. The open-source version gives you complete control over your memory infrastructure.
+Mem0 Open Source ships with capabilities that adapt memory behavior for production workloads—async operations, graph relationships, multimodal inputs, and fine-tuned retrieval. Configure these features with code or YAML to match your application's needs.
 
-## Why Choose Mem0 Open Source?
+<Info>
+  Start with the <Link href="/open-source/python-quickstart">Python quickstart</Link> to validate basic memory operations, then enable the features below when you need them.
+</Info>
 
-Mem0 open-source provides a powerful, flexible foundation for AI memory management with these key advantages:
+## Choose your path
 
-1. **Complete Control**: Deploy and manage your own memory infrastructure with full customization capabilities. Perfect for organizations that need data sovereignty and custom integrations.
+<CardGroup cols={3}>
+  <Card title="Graph Memory" icon="network-wired" href="/open-source/features/graph-memory">
+    Store entity relationships for multi-hop recall.
+  </Card>
+  <Card title="Advanced Metadata Filtering" icon="filter" href="/open-source/features/metadata-filtering">
+    Query with logical operators and nested conditions.
+  </Card>
+  <Card title="Search with Reranking" icon="ranking-star" href="/open-source/features/reranker-search">
+    Boost search relevance with specialized models.
+  </Card>
+  <Card title="Async Memory Operations" icon="bolt" href="/open-source/features/async-memory">
+    Non-blocking operations for high-throughput apps.
+  </Card>
+  <Card title="Multimodal Support" icon="image" href="/open-source/features/multimodal-support">
+    Process images, audio, and video memories.
+  </Card>
+  <Card title="Custom Fact Extraction" icon="wand-magic-sparkles" href="/open-source/features/custom-fact-extraction-prompt">
+    Tailor how facts are extracted from text.
+  </Card>
+</CardGroup>
 
-2. **Flexible Architecture**: Choose from multiple vector databases (Pinecone, Qdrant, Weaviate, Chroma, PGVector), graph stores (Neo4j, Memgraph), and embedding models to fit your specific needs.
+<CardGroup cols={3}>
+  <Card title="Custom Memory Updates" icon="arrows-rotate" href="/open-source/features/custom-update-memory-prompt">
+    Control memory refinement with custom instructions.
+  </Card>
+  <Card title="REST API" icon="code" href="/open-source/features/rest-api">
+    HTTP endpoints for language-agnostic integrations.
+  </Card>
+  <Card title="OpenAI Compatibility" icon="message-bot" href="/open-source/features/openai_compatibility">
+    Drop-in replacement for OpenAI chat endpoints.
+  </Card>
+</CardGroup>
 
-3. **Advanced Memory Organization**: Organize memories using `user_id`, `agent_id`, and `run_id` parameters for sophisticated multi-agent, multi-session applications with precise context control.
+<Tip>
+  Looking for managed features instead? Compare self-hosting vs managed in the <Link href="/platform/platform-vs-oss">Platform vs OSS guide</Link>.
+</Tip>
 
-4. **Rich Integration Ecosystem**: Seamlessly integrate with popular frameworks like LangChain, LlamaIndex, AutoGen, CrewAI, and Vercel AI SDK.
+## Keep going
 
-## Core Features
-
-### Memory Management
-- **Synchronous & Asynchronous Operations**: Choose between sync and async memory operations based on your application needs
-- **Smart Memory Retrieval**: Intelligent search and retrieval with semantic understanding
-- **Advanced Reranking**: Improve search relevance with Zero Entropy, LLM-based, or custom reranking models
-- **Memory Persistence**: Long-term storage with automatic optimization and cleanup
-
-### Advanced Organization
-- **User Context**: Organize memories by user for personalized experiences
-- **Agent Isolation**: Separate memories by AI agent for specialized knowledge domains
-- **Session Tracking**: Use run IDs to maintain context across different conversation sessions
-
-### Flexible Storage
-- **Vector Databases**: Support for Pinecone, Qdrant, Weaviate, Chroma, and PGVector
-- **Graph Stores**: Neo4j and Memgraph integration for relationship-based memory
-- **Embedding Models**: Multiple embedding providers for optimal performance
-
-## Getting Started
-
-Choose your preferred approach:
-
-- **[Python Quickstart](../python-quickstart)**: Get started with Python SDK
-- **[Node.js Quickstart](../node-quickstart)**: Use Mem0 with Node.js/TypeScript
-- **[Examples](/examples)**: Explore real-world use cases and implementations
-
-## Next Steps
-
-- Explore [specific features](./async-memory) in detail
-- Learn about [graph memory](./graph-memory) capabilities
-- Set up [vector databases](/components/vectordbs/overview) and [LLM integrations](/components/llms/overview)
-- Check out our [examples](/examples) for practical implementations
-- Join our [Discord community](https://mem0.dev/DiD) for support
-
-We're excited to see what you'll build with Mem0 open-source.
+<CardGroup cols={2}>
+  <Card
+    title="Configure Components"
+    description="Choose your LLM, embedder, vector store, and reranker with YAML or code."
+    icon="sliders"
+    href="/open-source/configuration"
+  />
+  <Card
+    title="Explore Cookbooks"
+    description="Follow production-ready examples that combine multiple features."
+    icon="book"
+    href="/cookbooks/overview"
+  />
+</CardGroup>