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Enhance README key features formatting

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Updated key features section with improved formatting and descriptions.
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@ -38,17 +38,49 @@ TrustGraph provides an event-driven data-to-AI platform that transforms raw data
TrustGraph is not just another AI framework but a complete, production-ready platform that bridges the gap between raw data and intelligent, adaptable agent deployments.
- **AI-Ready Data Transformation**: Convert unstructured and structured (bring your own schema) data into AI-optimized formats.
- **Automated Knowledge Graph Construction**: Transform unstructured data into interconnected knowledge graphs that capture relationships, context, and meaning.
- **Semantic Retrieval**: TrustGraph combines multiple retrieval methods optimized for each data type and use case.
- **Event Driven**: Built with Apache Pulsar for high-throughput and reliable messaging
- **Datastore Orchestration**: Deploy stores like Apache Cassandra, Neo4j, Qdrant, Milvus, Memgraph, or FalkorDB for structured and unstructured data storage.
- **Data Sovereignty**: Deploy the entire stack—data pipelines, knowledge graphs, vector stores, and LLMs—on-premises, in your VPC, or across hybrid environments.
- **Private LLM Inferencing**: In addition to support for all major LLM APIs, deploy and manage open models connected to all of the agentic data infrastructure.
- **Agentic GraphRAG**: Deploy intelligent agents with context awareness. Bring your own ontology for easy integration into interconnected systems.
- **Production Ready**: Containerized deployment with Docker/Kubernetes support. Built for enterprise scale with monitoring, observability, and management.
- **MCP Integration**: Native support for MCP enables standardized agent communication with third-party tools and services while maintaining data sovereignty.
- **Full Stack Visibility**: 3D visualization of knowledge graphs. Grafana dashboard for observability.
- **AI-Ready Data Transformation**
*Convert unstructured and structured (bring your own schema) data into AI-optimized formats*.
- **Automated Knowledge Graph Construction**
*Transform unstructured data into interconnected knowledge graphs that capture relationships, context, and meaning*.
- **Semantic Retrieval**
*TrustGraph combines multiple retrieval methods optimized for each data type and use case*.
- **Event Driven**
*Built with Apache Pulsar for high-throughput and reliable messaging*.
- **Datastore Orchestration**
*Deploy stores like Apache Cassandra, Neo4j, Qdrant, Milvus, Memgraph, or FalkorDB for structured and unstructured data storage*.
- **Data Sovereignty**
*Deploy the entire stack—data pipelines, knowledge graphs, vector stores, and LLMs—on-premises, in your VPC, or across hybrid environments*.
- **Private LLM Inferencing**
*In addition to support for all major LLM APIs, deploy and manage open models connected to all of the agentic data infrastructure*.
- **Agentic GraphRAG**
*Deploy intelligent agents with context awareness. Bring your own ontology for easy integration into interconnected systems*.
- **Production Ready**
*Containerized deployment with Docker/Kubernetes support. Built for enterprise scale with monitoring, observability, and management*.
- **MCP Integration**
*Native support for MCP enables standardized agent communication with third-party tools and services while maintaining data sovereignty*.
- **Full Stack Visibility**
*3D visualization of knowledge graphs. Grafana dashboard for observability*.
## Why TrustGraph?