Kai Extends Autonomous Defense Platform to the External Attack Surface and Launches Kai Labs

SAN JOSE, Calif., November 11, 2026 - Kai, the company behind the first agentic AI cybersecurity platform designed to execute security work end-to-end at machine speed, today announced External Attack Surface Management (EASM), now available on the Kai Autonomous Defense Platform. The company also launched Kai Labs, an expanded research team focused on the hardest open problems where AI meets security.

Most exposure management programs only see inside, so they miss the exposures attackers find first. With EASM, Kai unifies internal and external exposures into a single remediation plan, accelerating the path to zero. The external view sharpens what counts as real risk and lets teams address exposures comprehensively from one platform.

"Attackers start outside, and for most organizations the outside is the part they understand least," said Dr. Damiano Bolzoni, co-founder and CTO of Kai. "Extending our platform to the external attack surface means teams see their exposure the way an attacker does and fix it in the same place they manage everything else."

Kai unifies internal and external exposures into a single remediation plan

Many teams manage external and internal exposure with different tools, and the data from each is not integrated. Analysts reconcile external findings with internal data by hand to determine ownership, risk, and priority, which slows security down.

With EASM, Kai brings both surfaces into one platform and a single dataset, so external and internal exposure can be analyzed together at machine speed. The result is a clearer view of which exposures are real risk and single plan to close them. That matters because the external attack surface changes every day: new cloud services, forgotten subsidiaries, test sites left online, and APIs and AI services stood up without a security review.

Key capabilities include:

• Discovery and attribution: Discovers the internet-facing assets tied to an organization's domains, including assets that CMDBs and internal asset inventories commonly miss.

• Exposed AI infrastructure: Finds LLM endpoints, MCP servers, and vector databases.

• API visibility: Breaks published API definitions down into the individual endpoints they expose.

• Attacker-style investigation: Investigates and uncovers exposures the same way an attacker would.

• One asset record, one queue: Every external exposure joins the same asset record, aligns to the same owners, and is fixed through the same workflow as internal vulnerabilities and misconfigurations.

Introducing Kai Labs

Alongside EASM, Kai is launching Kai Labs, an expanded research team that tackles the hardest open problems where AI meets security. Kai Labs tests its ideas in real security programs, not just the lab.

Kai Labs is led by Kylie McClanahan, PhD, Research Director, whose career spans vulnerability management, prioritization, and remediation. The team pairs AI scientists with security researchers in detection, application security, offensive research, and AI red teaming.

Its first research areas are offensive learning, autonomous action, decision models, trusted autonomy, and security context, spanning how AI attackers learn, how fixes are generated and verified, and how defenders can trust autonomous action. Kai Labs publishes its findings through blogs, conference talks, and peer-reviewed papers.

About Kai

Kai is the AI company rebuilding cybersecurity for the machine-speed era. Trusted by Fortune 500 and Global 2000 enterprises, the Kai Autonomous Defense Platform replaces fragmented tools and human-limited workflows with agentic AI that works continuously across exposure management, cyber asset management, and detection intelligence. It contextualizes, reasons, and acts at machine speed and enterprise scale. What takes human-led teams weeks, Kai executes in minutes and hours, driving risk toward zero through autonomous remediation. Human defenders don't just keep up. They become superhuman.