Clearly AI GTM brain

category

market profile

• text: Security reviews struggle to keep pace with product changes and often start with manual information gathering.
• text: Enterprise buyers also need privacy, vendor risk and AI governance reviews with a defensible audit trail.

personas

• title: Head of application security
  pains:

  • A growing review backlog leaves new features shipping without consistent threat modeling
  • Security engineers spend time collecting architecture context instead of evaluating risks
• title: Privacy and governance lead
  pains:

  • Must assess data flows and AI systems against policy while documenting decisions for audit
  • Separate review workflows duplicate intake and context
• title: Product security engineer
  pains:

  • Must chase developers for design documents and verify remediation across tickets and code

icp

• text: Large software-producing enterprises with dedicated application security and privacy teams and frequent product releases.
• text: Organizations with Jira, code repositories and documented policies whose reviews span products, vendors and AI systems.

message pillars

• text: Extend review coverage to match software delivery volume.
• text: Generate a contextual first draft from existing engineering artifacts.
• text: Give reviewers evidence and a defensible trail for each finding.

objections

• objection: AI might miss threats or invent findings.
  response: Pilot on previously reviewed systems; have security engineers challenge the cited findings and compare gaps before expanding coverage.
• objection: Connecting repositories and sensitive designs creates security risk.
  response: Review access controls, data handling and vendor governance with the security team before integration.

competitors

• name: ThreatModeler
  why: Automates enterprise threat modeling and security design review.
• name: Security Compass
  why: SD Elements supports security requirements and threat modeling across development.
• name: Microsoft Threat Modeling Tool
  why: A free alternative for teams creating threat models manually.

influencers

• name: Emily Choi-Greene
  url: https://choigreene.com/guides/our-yc-application
  why: Co-founder and product security practitioner who publicly describes the company's founding and sales approach.

keywords

• automated threat modeling
• application security review automation
• privacy impact assessment software
• AI security review
• product security review backlog
• vendor risk review automation

voice

• Technical and direct
• Pragmatic about reviewers and auditability

signals

• text: Rapid release growth or an expanding security review queue indicates demand for more review capacity.
• text: Launching AI products or formalizing vendor and privacy reviews creates adjacent assessment workloads.

stack

• Jira
• GitHub
• Slack
• MCP

hiring

• Enterprise Account Strategist

pricing

motion

channels

• founder-led sales
• security consultants
• events
• content

confidence

Founders

• name: Emily Choi-Greene
  title: Founder/CEO
  role: CEO
  bio: Founder/CEO at Clearly AI. Previously, Emily owned data security and privacy at Moveworks. Before that, she spent 5 years at Amazon, where she led Alexa AI Security. Emily performed hundreds of security and privacy reviews, from Moveworks' AI data lifecycle to Alexa's machine learning compute platform (used by 5000+ ML scientists). Emily graduated with High Honors in Computer Science from Dartmouth College.
• name: Joe Choi-Greene
  title: Founder/CTO
  role: CTO
  bio: Founder/CTO at Clearly AI. Previously, Joe was a sr. software engineer at Amazon. Joe led the satellite telemetry team at Project Kuiper and built exabyte scale datalakes at Alexa. Joe graduated from Carnegie Mellon University with a degree in computer science.