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Sequoia Capital·Sequoia Capital Perspectives·RSS·2026.03.10

Sequoia, Scanner 파트너십 — 모든 로그가 이야기를 한다, 빨리 찾을 수만 있다면

Partnering with Scanner: Every Log Tells a Story—If You Can Find It Fast Enough

원문 보기 (영문) →
한국어 요약 번역

By Bogomil Balkansky. 2026년 3월 10일 발행.

문제

최근 Sequoia가 차세대 보안 인프라를 리서치하며 실리콘밸리 최고 기술 회사들의 CISO와 보안 엔지니어들에게 물었다 — "가장 큰 두통이 뭡니까?"

답은 일관됐다 — "우리는 보관할 여유가 없는 로그에 빠져 죽고, 검색할 여유가 없는 로그에 대해 눈이 멀고 있다."

현실: 보안팀은 모든 API 호출·로그인 이벤트·네트워크 연결을 분석해야 한다. 위협 조사를 위해 1년 이상 거슬러 올라가야 한다. 그런데 Splunk 같은 SIEM에 모두 저장하면 CISO 예산의 15%를 잡아먹는다. 그래서 회사들은 최근 10-30일치만 SIEM에 두고 나머지는 S3에 "freeze"한다 — 사실상 검색 불가능.

Scanner의 해법

Scanner 창업자 Cliff Crosland와 Steven Wu의 통찰: "객체 저장소(S3)를 위해 처음부터 설계된 로그 검색 엔진은 어떻게 생겼을까?"

답은 S3의 파일 영역에 필드 값을 직접 매핑하는 inverted index. 수십억 행을 훑는 대신, 각 쿼리를 관련 슬라이스로만 좁힌다.

  • 1페타바이트 로그가 인터랙티브해진다
  • 몇 시간 걸리던 쿼리가 몇 초 내 실행
  • 스트리밍 탐지 엔진이 매일 수십 테라바이트를 수백 개 룰로 연속 검사

고객

현재 사용 중인 회사들: Notion, Ramp, Benchling, Confluent, Lemonade, BeyondTrust. Benchling은 다른 제품의 10배 가격 인상 후 Scanner로 교체 — "가장 좋은 기술 결정 중 하나"라고 평가. Ramp는 보안 로그로 시작해 애플리케이션 로그로 확장하며 SIEM 청구서 절감.

가장 인상적인 부분

Notion의 탐지·대응팀은 Scanner로 보안 조사를 자율 실행하는 내부 AI 에이전트를 만들었다. MCP 출시 몇 주 만에 Scanner 고객의 약 1/3이 프로덕션에서 사용하기 시작했고, 현재 플랫폼 쿼리의 80%가 에이전트에서 발생. 프로토타입이 아니라 예정보다 빨리 도착한 미래.

Sequoia가 Scanner Series A를 리드하며, 너무 오래 재발명을 기다린 시장의 미래를 정의하는 데 함께한다.

English Original

Partnering with Scanner: Every Log Tells a Story—If You Can Find It Fast Enough

Cliff and Steven are making petabytes of security data searchable in seconds, and opening the door to a new era of AI-driven security operations.

Steven and Cliff.

A while back, I was deep in research on the next generation of security infrastructure, talking to CISOs and security engineers at some of the most technically sophisticated companies in Silicon Valley. I asked them all the same question I’d asked a decade earlier when I worked in enterprise software: What’s your biggest headache? The consistency of their answers surprised me. “We drown in logs we can’t afford to keep,” as one security leader put it, “and go blind on the logs we can’t afford to search.”

Enterprise security today is a story of impossible choices. The tools that teams rely on generate enormous amounts of log data—every API call, every login event, every network connection. To investigate cyber threats, they need all of it, often going back a year or more. But storing everything in a SIEM like Splunk is prohibitively expensive; costs could easily consume 15% of a CISO’s entire budget. Instead, companies make a compromise: they keep only the most recent 10 to 30 days of logs in their SIEM and park the rest in Amazon S3, where storage is cheap, but the data is effectively frozen. When a breach, a compliance audit, or a forensic investigation happens, security teams discover too late that the evidence they need is out of reach, opaque and unsearchable. 

I first heard about Scanner from a member of the security team at Temporal, one of our portfolio companies, who called it, “crazy fast.” I looked into it, and reached out to Cliff Crosland right away.

What Cliff and his co-founder Steven Wu have built is elegant in its insight. They asked: what would a log search engine look like if you designed it from scratch for object storage? The answer was a purpose-built inverted index that maps field values directly to file regions in S3. Rather than combing through billions of rows, Scanner narrows each query to only the relevant slices of data. A petabyte of logs becomes interactive. Queries that took hours now run in seconds. And a streaming detection engine runs hundreds of detection rules continuously across tens of terabytes a day, without re-scanning the world for each one.

Cliff and Steven are exactly the kind of founders we look for. Both Stanford CS alums, they were engineering leads together at Accompany (acquired by Cisco), where they built core data infrastructure under demanding, production-scale conditions. They have an obsession with performance that borders on the philosophical; they don’t tolerate systems that feel slow. And they have the expertise to build something better.

What’s most striking about Scanner isn’t the technology—though that is genuinely impressive. It’s the customers. The companies using Scanner today read like a who’s who of the cloud native world: Notion, Ramp, Benchling, Confluent, Lemonade, BeyondTrust. And they’re not just using it—they love it. Benchling replaced another product after a forced tenfold price increase, and their head of security engineering called it one of the best technical decisions their team had made. Ramp started with security logs and then expanded to application logs, reducing their SIEM bill in the process. Notion’s detection and response team built an internal AI agent that autonomously runs security investigations using Scanner. 

That last example signals what’s to come. We are entering a new era of security operations, where AI agents will do much of the investigative work that today consumes hours of human time. But agents need to rapidly iterate, ask questions and follow threads; queries can’t take minutes, much less hours. Scanner’s speed is enabling these agentic security workflows across a wide range of companies: within weeks of their MCP release, nearly a third of Scanner’s customers were already using it in production, and agents now account for 80% of queries on the platform. That is not a prototype or a promising beta. That is the future arriving ahead of schedule.

Sequoia is proud to lead Scanner’s Series A, and we’re thrilled to partner with Cliff, Steven and their team as they work to transform a market overdue for reinvention. Scanner is winning hearts and minds among the most technically forward organizations today, and together, they will define the next decade of security infrastructure.

The post Partnering with Scanner: Every Log Tells a Story—If You Can Find It Fast Enough appeared first on Sequoia Capital.

Sequoia, Scanner 파트너십 — 모든 로그가 이야기를 한다, 빨리 찾을 수만 있다면 — 인텔리뷰 | 인텔리뷰 Inteliview