Tenzir is a security-native data pipeline platform designed to help security teams collect, transform, normalize, enrich, and route security data across their infrastructure. The platform supports deployments across hyperscaler environments, on-premises/self-hosted setups, and SaaS configurations. At its core, Tenzir provides a pipeline fabric that ingests data from over 150 integrations — including major cloud providers (AWS, Azure, Google Cloud), SIEMs, data lakes, and security tools — and enables users to shape and route that data to destinations such as SIEM, SOAR, XDR, and data lake systems. The platform supports normalization to industry-standard schemas including OCSF (Open Cybersecurity Schema Framework), ASIM, and ECS. Key capabilities include parsing unstructured data into structured formats, data volume optimization to reduce storage costs, anonymization and masking for compliance, threat enrichment using threat intelligence and asset/vulnerability context, and streaming detection using Sigma rules, YARA, and Python. Data can be stored in Parquet format to object storage and replayed from rest back into motion for retroactive analysis. Tenzir incorporates AI-powered automation, including an open-source MCP (Model Context Protocol) server that accelerates data source onboarding and pipeline creation. The platform targets security engineers and cyber defenders who need to manage complex, multi-source security data flows without vendor lock-in. It is positioned as a Security Data Pipeline Platform (SDPP), a category it actively promotes through research content on its site.