Cloud-Native Security Data Lake with Real-Time Threat Detection on S3

Scanner is a cloud-native security data lake purpose-built for organizations drowning in security telemetry. Instead of duplicating data into a proprietary SIEM, Scanner indexes logs directly in the customer's own Amazon S3 buckets — eliminating ingest fees, vendor lock-in, and the schema rigidity that forces teams to drop or sample data. Full-text search runs across petabytes in seconds, and a streaming query engine evaluates detections continuously against live data, surfacing threats in real time without sampling.

Headquartered in San Francisco and backed by Sequoia Capital with a $22M Series A, Scanner is engineered for modern detection engineering and AI-driven security workflows. Native integrations cover AWS CloudTrail, Azure, Google Cloud, Okta, GitHub, Tines, PagerDuty, and dozens more, with programmatic API access that lets security teams wire Scanner into automated pipelines, SOAR playbooks, and AI agents. The platform's economics make it practical to retain full-fidelity logs for the long horizons compliance and incident response require — without the per-gigabyte penalties traditional SIEMs impose.