Monad is a security data engineering platform that focuses on the collection, storage, processing, transformation, and enrichment of security telemetry data. The platform is designed to help security teams manage the complexity of handling large volumes of security data across its full lifecycle. Core capabilities revolve around: - Data Collection & Storage: Ingesting security telemetry from various sources and storing it in structured formats, including security data lakes. - Data Processing: Applying logic and rules to raw security data to make it usable for downstream analysis. - Data Transformation: Converting security data between formats or schemas to normalize and standardize it. - Data Enrichment: Augmenting security data with additional context to improve signal quality and analytical value. - Signal Filtering & Routing: Allowing users to filter out noise and route relevant security data to the appropriate destinations. The platform targets security engineers and operations teams who need to build and maintain pipelines for security telemetry. It addresses common challenges in security data engineering such as high data volumes, format inconsistencies, and signal-to-noise ratio issues.