Cybersecurity startup Scanner has announced raising $22 million in a Series A funding round led by Sequoia Capital, with additional support from CRV, Mantis VC, and angel investors.
Founded in 2022, San Francisco-based Scanner helps organizations build a cloud-native security data lake for fast threat hunting and continuous detection and response.
It connects to existing tools and security stack and offers a Model Context Protocol (MCP) server that connects AI agents to organizations’ data lakes to power security operations.
Scanner’s solution relies on inverted indexes built at ingestion time to run scans on the data that matters. It scales up when running queries and scales down when idle, to cut costs.
The AI agents, Scanner says, were designed to correlate across data sources and return smart summaries, supporting interactive investigations, detection engineering, and autonomous response workflows.
According to Scanner, its solution can deliver responses in a fraction of the time required by traditional SIEM solutions because it indexes data directly where it lives and runs detections continuously on the full stream.
“Security teams generate massive amounts of data but can only afford to search a fraction of it. Scanner has built a fundamentally new approach to this problem, which enables companies to move into the agentic era of cybersecurity. AI is notoriously data hungry, and Scanner is the only technology on the market today that manages security data at AI scale,” said Sequoia Capital partner Bogomil Balkansky.
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