Artemis Security

Artemis Security did not enter quietly. It stepped in with conviction, capital, and a clear read on where security was already failing. In a market saturated with tools that generate noise faster than answers, Artemis Security positions itself as the system that restores clarity, and that signal is already moving through the startup ecosystem with speed.

Founded in 2025 and based in New York, the company is led by Shachar Hirshberg and Dan Shiebler, two builders who have already shaped the systems they are now replacing. Shachar Hirshberg scaled through Demisto before its acquisition, led engineering at Palo Alto Networks, and ran Amazon GuardDuty at AWS. Dan Shiebler, with a PhD in AI from Oxford, built machine learning systems at Twitter and led ML at Abnormal Security. This is not a first swing. This is a second act with memory.

In April 2026, Artemis Security emerged from stealth with $70M across seed and Series A, led by Felicis with participation from First Round Capital, Brightmind Partners, Theory Ventures, Lockstep, and Two Sigma Ventures. The investor bench matters, but the operator density matters more. Backing from founders of Demisto and Abnormal Security, alongside former Splunk leadership and senior operators from CrowdStrike, Palo Alto Networks, Microsoft, and Okta, signals something deeper than capital. It reflects alignment around a shared problem that has been building for years inside the startup ecosystem and enterprise security alike.

The problem is not subtle. Attackers are already operating at machine speed, while most security teams are still navigating alert queues built for a different era. Artemis Security closes that gap with an AI-native platform designed to understand, not just observe. It builds a dynamic model of each environment across users, machines, cloud workloads, and applications, then reconstructs full attack narratives instead of pushing fragmented alerts downstream. This is not incremental improvement. It is a shift from signal overload to decision clarity.

The impact shows up where it counts. Customers are reporting up to a 94% reduction in time to detect and respond to meaningful threats. That compresses what used to take hours into minutes, sometimes seconds. In a market where speed defines outcome, that delta is not cosmetic. It is existential. Artemis Security is already operating in production, processing large-scale telemetry across enterprise environments in technology and financial services, proving that this model is not theoretical.

What separates Artemis Security is not just architecture, but orientation. A per-customer data model that adapts in real time. AI that learns business context, not just anomalies. A system that treats investigation as the product, not a byproduct. As more environments flow through the platform, the system compounds in intelligence, creating a feedback loop that is difficult to replicate and increasingly valuable across the startup ecosystem.

Inside the company, the culture reflects the product. High ownership, tight iteration loops, and collaboration across engineering, AI, and security disciplines grounded in real-world incidents. This is a team built for builders. Artemis Security is hiring across engineering, AI, and security roles for operators who want proximity to real problems and real outcomes.

For founders, investors, and technologists tracking where infrastructure is being rewritten, Artemis Security is not just another entrant. It is a signal. The product is live, the capital is deployed, and the direction is clear.