BusinessWednesday, April 15, 2026· 2 min read

Gitar Raises $9M to Use AI Agents for Securing AI-Generated Code

TL;DR

Gitar, an AI startup, emerged from stealth with $9 million to deploy agent-driven code review that catches vulnerabilities in both human- and AI-written code. The approach promises faster, scalable security checks that help developers safely adopt AI-assisted coding.

Key Takeaways

  • 1Gitar launched from stealth with $9M to commercialize agent-based code security.
  • 2The company uses AI agents to review code — including AI-generated snippets — to find vulnerabilities and insecure patterns.
  • 3Agent-driven reviews can scale with modern development workflows and help teams adopt AI coding tools more safely.
  • 4Early funding will accelerate product development and deployment to benefit developers and organizations relying on AI-assisted code.

Gitar emerges from stealth to secure the next wave of AI-created code

Gitar has officially come out of stealth with a $9 million raise, launching a focused effort to secure codebases where AI-assisted code generation is now common. The startup applies AI agents to automatically review code and flag vulnerabilities, misconfigurations, and risky patterns — closing a rising gap as more developers rely on generative tools.

The company’s agent-based approach lets security checks run continuously and contextually across pull requests and CI/CD pipelines. Rather than replacing existing tooling, these agents augment developer workflows, offering actionable findings and remediation guidance so teams can fix issues earlier and ship with greater confidence.

Backed by fresh funding, Gitar plans to scale its product and integrations so organizations of all sizes can benefit. By focusing on both human-authored and AI-generated code, the startup helps prevent a new class of supply-chain and deployment risks that could arise as generative coding becomes ubiquitous.

Why this matters:

  • Improves developer productivity by automating security reviews within existing workflows.
  • Addresses vulnerabilities specific to AI-generated code, helping teams adopt generative tools safely.
  • Funding accelerates product maturation and broader adoption, bringing practical security benefits to more projects.

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