Corridor Raises $25M to Embed Security Into AI Coding Workflows
Corridor, a San Francisco security platform, closed a $25 million Series A round led by Felicis Ventures at a $200 million valuation. The company builds tools to catch vulnerabilities as AI generates code, rather than after development finishes.
The funding round included Conviction, Timeless, Artisanal Ventures, Lux Capital, Sunflower Capital, and Datadog, plus angel investors from Anthropic, OpenAI, Cursor, Cognition, Factory, and Lovable.
The Problem: Traditional Security Doesn't Scale With AI Coding
AI coding tools generate code faster and in greater volume than humans can review. Security teams still rely on post-development scanning and code review-methods designed for human-paced development.
Corridor embeds real-time security controls directly into AI coding workflows. The platform flags issues at the moment code is generated, before it enters the broader development pipeline.
How It Works
The platform integrates with AI coding environments like Cursor and Factory, providing immediate feedback during development and code review. It supports use cases ranging from experienced developers managing teams of autonomous coding agents to non-technical teams building internal applications with AI tools.
Corridor's leadership includes CEO Jack Cable, CTO Ashwin Ramaswami, and Chief Product Officer Alex Stamos, who bring backgrounds in cybersecurity and AI.
What's Next
Corridor plans to expand its Agentic Coding Security Management platform and deepen integrations across developer tools. The company will invest in engineering, research, and cybersecurity teams.
Cable said: "Secure by design can't just be a slogan, it has to be how software actually gets built. As AI revolutionizes coding, security has to be embedded at the moment code is created, not bolted on later."
For developers working with AI coding tools, understanding how security integrates into these workflows is becoming essential. Consider exploring AI Learning Path for Software Developers to deepen your knowledge of secure AI-driven development practices.
Cybersecurity professionals should also consider how AI changes threat detection and vulnerability prevention. The AI Learning Path for Cybersecurity Analysts covers these evolving skill requirements.
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