Databahn Reef is an AI-powered security insights layer designed to transform raw security log data into actionable intelligence for security operations centers (SOCs) and security teams. The platform addresses challenges related to data overload, siloed information, and fragmented security data across multiple sources. Reef operates as a data foundation that sits between security data sources and analysis tools, providing conversational natural language querying capabilities to search across security logs. The platform uses AI-driven enrichment and correlation to generate insights from streaming data in real-time, enabling security teams to identify threats, vulnerabilities, and anomalous behavior patterns. The solution decouples insight generation from SIEM ingestion, allowing organizations to reduce costs associated with traditional SIEM platforms while maintaining or improving analytical capabilities. Reef can be accessed directly through its interface or queried via other security products and tools, acting as an open data layer. The platform performs AI-powered pattern detection and learning on log data, automatically translating raw security data into contextualized insights. It supports multi-source correlation and provides explanations for detected patterns and anomalies. Reef leverages Model Context Protocol (MCP) to connect with other AI solutions for insight and intelligence access. The system is designed to reduce time-to-insight for security investigations, enable faster threat identification and severity evaluation, and provide real-time visibility into security events without requiring data movement between systems.